US9294333B1 - System and method for privacy setting differentiation detection - Google Patents

System and method for privacy setting differentiation detection Download PDF

Info

Publication number
US9294333B1
US9294333B1 US14/453,319 US201414453319A US9294333B1 US 9294333 B1 US9294333 B1 US 9294333B1 US 201414453319 A US201414453319 A US 201414453319A US 9294333 B1 US9294333 B1 US 9294333B1
Authority
US
United States
Prior art keywords
privacy settings
user
social network
privacy
service
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
US14/453,319
Inventor
Jessica Staddon
Jonathan S. McPhie
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Google LLC
Original Assignee
Google LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Google LLC filed Critical Google LLC
Priority to US14/453,319 priority Critical patent/US9294333B1/en
Assigned to GOOGLE INC. reassignment GOOGLE INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: MCPHIE, JONATHAN S., STADDON, JESSICA
Application granted granted Critical
Publication of US9294333B1 publication Critical patent/US9294333B1/en
Assigned to GOOGLE LLC reassignment GOOGLE LLC CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: GOOGLE INC.
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/04Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
    • H04L63/0407Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the identity of one or more communicating identities is hidden
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/10Network architectures or network communication protocols for network security for controlling access to devices or network resources
    • H04L63/102Entity profiles
    • H04L29/06639
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60Protecting data
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60Protecting data
    • G06F21/62Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245Protecting personal data, e.g. for financial or medical purposes
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/01Social networking
    • H04L29/08693
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network arrangements or protocols for supporting network services or applications
    • H04L67/50Network services
    • H04L67/55Push-based network services

Definitions

  • the specification relates to social networks.
  • the present specification relates to privacy settings on social networks.
  • the present specification also relates to generating and sending a notification to a first social network user when the user's privacy settings of the first social network differ from the user's privacy settings in at least one other social network.
  • Social networks are becoming an increasingly popular way for people to stay connected. This increasing popularity of social networks has given rise to social network services that have developed various ways users of the social network can communicate and share information. Users within a social network can send each other messages, view other users' activities and share personal information, including personal photographs and videos. Social networking services can provide a forum for users to remain in close contact despite geographic distance or uncoordinated schedules. Social network users are typically able to adjust the amount and type of information they choose to share and how and with whom that information is shared. However, for users belonging to multiple social networks, it may be difficult for the users to monitor the privacy settings of each social network, remember the different privacy settings of each social network, or even realize that each social network's privacy settings are different.
  • a system and method are provided for generating a notification of privacy settings difference.
  • the system includes a request receiver engine, privacy settings retrieval engine, privacy settings differentiator engine, differentiation display engine and an optional privacy settings adjustment engine.
  • the request receiver engine for receives a request.
  • the privacy settings retrieval engine receives a first set of privacy settings of a user from a first social network and a second set of privacy settings of the user from at least one other social network.
  • the privacy settings differentiator engine compares the privacy settings of the first social network to those of the of the at least one other social network and, responsive to detecting a difference between the first set of privacy settings and the second set of privacy settings, prompts the differentiation display engine to generate a notification.
  • the notification is sent to the user for display and includes an indication that the difference has been detected.
  • the request is the user's login request that is sent to the first social network.
  • the request is the user's request to edit one or more privacy settings of the first social network.
  • the request is the user selecting a button or hypertext link on the first social network.
  • the difference exists when the privacy setting of the first set of privacy settings is less restrictive than the privacy setting of the second set of privacy settings.
  • the notification may include a variety of information and features.
  • the notification identifies at least one other social network having the detected difference from the first social network.
  • the notification includes the detected difference between the first set of privacy settings and the second set of privacy settings.
  • the notification allows the user to request to view, or edit, one or more of the privacy settings of the first social network.
  • the privacy settings adjustment engine receives the user's request to view, or edit, the privacy settings of the first social network; and sends the user to a webpage on the first social network where the privacy settings are typically displayed, or edited.
  • the privacy settings adjustment module receives the user's request to edit and one or more edits to the user's privacy settings of the first social network; and updates the privacy settings of the first social network according to the edits received from the user.
  • FIG. 1 illustrates a block diagram of a system for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings in at least one other social network according to one embodiment.
  • FIG. 2 is a block diagram of a social network server in accordance with one embodiment.
  • FIG. 3 is a block diagram illustrating a differentiation detection module according to one embodiment.
  • FIG. 4 is a flow chart illustrating a method for detecting and notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network according to one embodiment.
  • FIG. 5 illustrates a storage device storing user data including the user's privacy settings according to one embodiment.
  • FIG. 6 is a graphic representation of an example of a user interface displaying a notification to the first social network user that one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network according to one embodiment.
  • FIG. 7 is a graphic representation of another example of a user interface displaying a notification to the first social network user that one or more of the user's privacy settings differ from the user's privacy settings on at least one other social network according to another embodiment.
  • a system and method for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network is described.
  • numerous specific details are set forth in order to provide a thorough understanding of the embodiments. It will be apparent, however, to one skilled in the art that the embodiments can be practiced without these specific details. In other instances, structures and devices are shown in block diagram form in order to avoid obscuring the embodiments.
  • the present embodiments are described in one embodiment below with reference to user interfaces and particular hardware. However, the present embodiments apply to any type of computing device that can receive data and commands, and any peripheral devices providing services.
  • the present embodiments also relate to an apparatus for performing the operations herein.
  • This apparatus may be specially constructed for the required purposes, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer.
  • a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, flash memories including USB keys with non-volatile memory or any type of media suitable for storing electronic instructions, each coupled to a computer system bus.
  • the embodiments can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements.
  • a preferred embodiment is implemented in software, which includes but is not limited to firmware, resident software, microcode, etc.
  • one embodiment can take the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by or in connection with a computer or any instruction execution system.
  • a computer-usable or computer readable medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
  • a data processing system suitable for storing and/or executing program code will include at least one processor coupled directly or indirectly to memory elements through a system bus.
  • the memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memories which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution.
  • I/O devices including but not limited to keyboards, displays, pointing devices, etc.
  • I/O controllers can be coupled to the system either directly or through intervening I/O controllers.
  • Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks.
  • Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.
  • FIG. 1 illustrates a block diagram of a system 100 for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings on at least one other social network according to one embodiment.
  • the illustrated embodiment of the system 100 for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings on at least one other social network includes user devices 115 a , 115 b , 115 n that are accessed by users 125 a , 125 b , 125 n and a third party server 107 .
  • the system 100 also includes social network servers 101 a , 101 b , 101 n . In the illustrated embodiment, these entities are communicatively coupled via a network 105 .
  • the user devices 115 a , 115 b , 115 n and social network servers 101 a , 101 b , 101 n in FIG. 1 are used by way of example. While FIG. 1 illustrates three devices, the present embodiment applies to any system architecture having one or more user devices and one or more social network servers associated with two or more social networks. Furthermore, while only one network 105 is coupled to the user devices, 115 a , 115 b , 115 n , the social network servers 101 a , 101 b , 101 n , and the third party server 107 , in practice any number of networks 105 can be connected to the entities. Furthermore, while only one third party application server 107 is shown, the system 100 could include one or more third party application servers 107 .
  • the social network server 101 a / 101 b / 101 n also contains a social network module 209 .
  • a social network is any type of social structure where the users are connected by a common feature. Examples include, but are not limited to, Orkut, Buzz, blogs, microblogs, and Internet forums.
  • the common feature includes friendship, family, a common interest, etc.
  • the common feature includes friendship, family, work, an interest, etc.
  • a social network can comprise one or more social network servers 101 a , 101 b , 101 n , for the purposes of describing the components and functionality of the system 100 , the below description describes the system 100 where each social network server 101 a / 101 b / 101 n belongs to and represents a different social network.
  • the network 105 enables communications between the user devices 115 a , 115 b , 115 n , the social network servers 101 a , 101 b , 101 n , and the third party application server 107 .
  • the network 105 can include links using technologies such as Wi-Fi, Wi-Max, 2G, Universal Mobile Telecommunications System (UMTS), 3G, Ethernet, 802.11, integrated services digital network (ISDN), digital subscriber line (DSL), asynchronous transfer mode (ATM), InfiniBand, PCI Express Advanced Switching, etc.
  • the networking protocols used on the network 105 can include the transmission control protocol/Internet protocol (TCP/IP), multi-protocol label switching (MPLS), the User Datagram Protocol (UDP), the hypertext transport protocol (HTTP), the simple mail transfer protocol (SMTP), the file transfer protocol (FTP), lightweight directory access protocol (LDAP), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Global System for Mobile communications (GSM), High-Speed Downlink Packet Access (HSDPA), etc.
  • the data exchanged over the network 105 can be represented using technologies and/or formats including the hypertext markup language (HTML), the extensible markup language (XML), etc.
  • links can be encrypted using conventional encryption technologies such as the secure sockets layer (SSL), Secure HTTP and/or virtual private networks (VPNs) or Internet Protocol security (IPsec).
  • SSL secure sockets layer
  • VPNs virtual private networks
  • IPsec Internet Protocol security
  • the entities can use custom and/or dedicated data communications technologies instead of, or in addition to, the ones described above.
  • the network 105 can also include links to other networks.
  • the network 105 is a partially public or a wholly public network such as the Internet.
  • the network 105 can also be a private network or include one or more distinct or logical private networks (e.g., virtual private networks, Wide Area Networks (“WAN”) and/or Local Area Networks (“LAN”)).
  • the communication links to and from the network 105 can be wireline or wireless (i.e., terrestrial—or satellite-based transceivers).
  • the network 105 is an IP-based wide or metropolitan area network.
  • the network 105 helps to form a set of online relationships between users 125 a , 125 b , 125 n , such as provided by one or more social networking systems including explicitly-defined relationships and relationships implied by social connections with other online users, where the relationships form a social graph.
  • the social graph can reflect a mapping of these users and how they are related.
  • a differentiation detection module 220 a is included in the social network server 101 a / 101 b / 101 n and is operable on the social network server 101 a / 101 b / 101 n .
  • the differentiation detection module 220 b is included in the third party application server 107 and is operable on the third party application server 107 .
  • the differentiation detection module 220 a / 220 b can be stored in any combination on the devices and servers.
  • the differentiation detection module 220 a / 220 b includes multiple, distributed modules that cooperate with each other to perform the functions described below. Details describing the functionality and components of the differentiation detection module 220 a of the social network server 101 a / 101 b / 101 n are explained in further detail below with regard to FIG. 3 .
  • the user devices 115 a , 115 b are coupled to the network 105 via signal lines 108 and 112 , respectively.
  • the user 125 a is communicatively coupled to the user device 115 a via signal line 116 .
  • the user 125 b is communicatively coupled to the user device 115 b via signal line 114 .
  • the third party application 107 is communicatively coupled to the network 105 via signal line 106 .
  • the social network servers 101 a , 101 b are coupled to the network 105 via signal lines 132 , 134 , respectively.
  • the social network servers 101 a , 101 b are each communicatively coupled to a data storage device 110 a / 110 b via a signal line 142 / 144 , respectively.
  • data storage 110 a / 110 b / 110 n stores data and information of users 125 a , 125 b , 125 n of the social network 101 a / 101 b / 101 n .
  • Such stored information includes user profiles and other information identifying each user 125 a / 125 b / 125 n of the social network 101 a / 101 b / 101 n .
  • Examples of information identifying users includes, but is not limited to, the user's name, contact information, sex, relationship status, likes, interests, links, education and employment history, location, political views, and religion.
  • the information stored in data storage 110 a / 110 b / 110 n also includes the user's list of current and past friends and the user's activities within the social network 101 a / 101 b / 101 n , such as anything the user posts within the social network 101 a / 101 b / 101 n and any messages that the user sends to other social network 101 a / 101 b / 101 n users.
  • the data and information stored by the data storage 110 a / 110 b / 110 n includes the user's 125 a / 125 b / 125 n privacy settings.
  • a storage device 214 see FIG.
  • the storage device 214 stores the data and information of the users 125 a , 125 b , 125 n of the social network 101 a / 101 b / 101 n discussed in relation to the data storage 110 a / 110 b / 110 n.
  • the user device 115 a , 115 b , 115 n is an electronic device having a web browser for interacting with one or more social network servers 101 a , 101 b , 101 n via the network 105 and is used by user 125 a , 125 b , 125 n to access information in the system 100 .
  • the user device 115 a , 115 b , 115 n can be, for example, a laptop computer, a desktop computer, a tablet computer, a mobile telephone, a personal digital assistant (PDA), a mobile email device, a portable game player, a portable music player, a portable music player, or any other electronic device capable of accessing a network.
  • PDA personal digital assistant
  • FIG. 2 is a block diagram of an embodiment of a social network server 101 a / 101 b / 101 n .
  • the social network server 101 a / 101 b / 101 n includes a network adapter 202 coupled to a bus 204 .
  • also coupled to the bus 204 are at least one processor 206 , memory 208 , a social network module 209 , a graphics adapter 210 , an input device 212 , a storage device 214 , and a differentiation detection module 220 a .
  • the functionality of the bus 204 is provided by an interconnecting chipset.
  • the social network server 101 a / 101 b / 101 n also includes a display 218 , which is coupled to the graphics adapter 210 .
  • the processor 206 may be any general-purpose processor.
  • the processor 206 comprises an arithmetic logic unit, a microprocessor, a general purpose controller or some other processor array to perform computations, provide electronic display signals to display 218 .
  • the processor 206 is coupled to the bus 204 for communication with the other components of the social network server 101 a / 101 b / 101 n .
  • Processor 206 processes data signals and may comprise various computing architectures including a complex instruction set computer (CISC) architecture, a reduced instruction set computer (RISC) architecture, or an architecture implementing a combination of instruction sets. Although only a single processor is shown in FIG. 2 , multiple processors may be included.
  • the social network server 101 a / 101 b / 101 n also includes an operating system executable by the processor such as but not limited to WINDOWS®, MacOS X, Android, or UNIX® based operating systems.
  • the memory 208 holds instructions and data used by the processor 206 .
  • the instructions and/or data comprise code for performing any and/or all of the techniques described herein.
  • the memory 208 may be a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, flash memory or some other memory device known in the art.
  • the memory 208 also includes a non-volatile memory such as a hard disk drive or flash drive for storing log information on a more permanent basis.
  • the memory 208 is coupled by the bus 204 for communication with the other components of the social network server 101 a / 101 b / 101 n .
  • the differentiation detection module 220 a is stored in memory 208 and executable by the processor 206 .
  • the social network module 209 is software and routines executable by the processor 206 to control the interaction between the social network server 101 a / 101 b / 101 n , storage device 214 and the user devices 115 a , 115 b , 115 n .
  • An embodiment of the social network module 209 allows users 125 a , 125 b , 125 n of user devices 115 a , 115 b , 115 n to perform social functions between other users 125 a , 125 b , 125 n of user devices 115 a , 115 b , 115 n within the system 100 .
  • the storage device 214 is any device capable of holding data, like a hard drive, compact disk read-only memory (CD-ROM), DVD, or a solid-state memory device.
  • the storage device 214 is a non-volatile memory device or similar permanent storage device and media.
  • the storage device 214 stores data and instructions for processor 208 and comprises one or more devices including a hard disk drive, a floppy disk drive, a CD-ROM device, a DVD-ROM device, a DVD-RAM device, a DVD-RW device, a flash memory device, or some other mass storage device known in the art.
  • the storage device 214 is used to store user profiles and other information identifying users 125 a , 125 b , 125 n of the social network 101 a / 101 b / 101 n . In some embodiments, such user data is stored in data storage 110 a / 110 b / 110 n.
  • the input device 212 may include a mouse, track ball, or other type of pointing device to input data into the social network server 101 a .
  • the input device 212 may also include a keyboard, such as a QWERTY keyboard.
  • the input device 212 may also include a microphone, a web camera or similar audio or video capture device.
  • the graphics adapter 210 displays images and other information on the display 218 .
  • the display 218 is a conventional type such as a liquid crystal display (LCD) or any other similarly equipped display device, screen, or monitor.
  • the display 218 represents any device equipped to display electronic images and data as described herein.
  • the network adapter 202 couples the social network server 101 a / 101 b / 101 n to a local or wide area network.
  • the differentiation detection module 220 a is software and routines executable by the processor 206 to notify a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network. Details describing the functionality and components of the differentiation detection module 220 a are explained in further detail below with regard to FIG. 3 .
  • a social network server 101 a / 101 b / 101 n can have different and/or other components than those shown in FIG. 2 .
  • the social network server 101 a can lack certain illustrated components.
  • a social network server 101 a / 101 b / 101 n lacks an input device 212 , graphics adapter 210 , and/or display 218 .
  • the storage device 214 can be local and/or remote from the social network server 101 a / 101 b / 101 n (such as embodied within a storage area network (SAN)).
  • SAN storage area network
  • the social network server 101 a / 101 b / 101 n is adapted to execute computer program modules for providing functionality described herein.
  • module refers to computer program logic utilized to provide the specified functionality.
  • a module can be implemented in hardware, firmware, and/or software.
  • program modules are stored on the storage device 214 , loaded into the memory 208 , and executed by the processor 206 .
  • Embodiments of the entities described herein can include other and/or different modules than the ones described here.
  • the functionality attributed to the modules can be performed by other or different modules in other embodiments.
  • this description occasionally omits the term “module” for purposes of clarity and convenience.
  • FIG. 3 is a block diagram of a portion of the social network server 101 a / 101 b / 101 n that includes the differentiation detection module 220 a , a processor 206 and a memory 208 , along with other modules and components recited in the description of FIG. 2 .
  • the third party application server 107 includes the differentiation detection module 220 b .
  • the differentiation detection module 220 a is software and routines executable by the processor 206 to notify a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network.
  • the below description describes the differentiation detection module 220 a .
  • the same description is also applicable to the functionality and components of the differentiation detection module 220 b .
  • the below description describes the differentiating behavior authentication module 220 a where the user's first social network is represented by social network server 101 a and each social network server 101 a , 101 b , and 101 n represents a different social network.
  • the same description is also applicable to the functionality and components of the differentiation detection module 220 a of 110 b , 110 n and 107 as long as one or more social network servers associated with two or more social networks are present.
  • the differentiation detection module 220 a comprises a request receiver engine 302 , a privacy settings retrieval engine 304 , a privacy settings differentiator engine 306 , and a differentiation display engine 308 .
  • the differentiation detection module also includes an optional privacy settings adjustment engine 310 .
  • the request receiver engine 302 is software and routines executable by the processor for receiving a request for access to information on a social network, wherein the information includes privacy settings information of a user and notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n .
  • the request receiver engine 302 is a set of instructions executable by the processor 206 to provide the functionality described below for receiving a request for access to information on a social network, wherein the information includes privacy settings information of a user and notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n .
  • the request receiver engine 302 is stored in the memory 208 of the social network server 101 a / 101 b / 101 n and is accessible and executable by the processor 206 . In either embodiment, the request receiver engine 302 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a / 101 b / 101 n via signal line 222 .
  • the request received by the request receiver engine 302 to notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n is the user's login request, i.e., the user, by logging into the first social network 101 a , automatically requests to be notified when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n .
  • the user's request to edit the user's privacy settings of the first social network 101 a is the request received by the request receiver 302 , i.e., the user, by changing one or more privacy settings of the first social network, automatically requests to be notified when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n .
  • the user can request to be notified when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n by clicking on a button or hypertext link, which is received by the request receiver engine 302 .
  • the privacy settings retrieval engine 304 is software and routines executable by the processor for receiving the user's privacy settings data from the first social network 101 a and from at least one other social network 101 b , 101 n to which the user belongs and sending that data to the privacy settings differentiator engine 306 .
  • the privacy settings retrieval engine 304 is a set of instructions executable by the processor 206 to provide the functionality described below for receiving the user's privacy settings data from the first social network 101 a and from at least one other social network 101 b , 101 n to which the user belongs and sending that data to the privacy settings differentiator engine 306 .
  • the privacy settings retrieval engine 304 is stored in the memory 208 of the social network server 101 a / 101 b / 101 n and is accessible and executable by the processor 206 . In either embodiment, the privacy settings retrieval engine 304 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a / 101 b / 101 n via signal line 224 .
  • the privacy settings retrieval engine 304 is also communicatively coupled, via the differentiation detection module 220 a of the each social network server 101 a / 101 b / 101 n to other social network servers 101 a , 101 b , 101 n .
  • the privacy settings retrieval engine 304 receives the user's privacy settings data from the storage device of one or more social networks 101 a , 101 b , 101 n to which the user belongs.
  • the privacy settings retrieval engine 304 receives the user's privacy settings data associated with one or more social networks 101 a , 101 b , 101 n to which the user belongs.
  • the privacy settings differentiator engine 306 is software and routines executable by the processor for receiving the privacy settings data received by the privacy settings retrieval engine 304 , comparing the privacy settings of the first social network 101 a and the privacy settings of at least one other social network 101 b , 101 n , and detecting differences.
  • the privacy settings differentiator engine 306 is a set of instructions executable by the processor 206 to provide the functionality described below for receiving the privacy settings received by the privacy settings retrieval engine 304 , comparing the privacy settings of the first social network 101 a and privacy settings of the at least one other social network 101 b , 101 n , and detecting differences.
  • the privacy settings differentiator engine 306 is stored in the memory 208 of the social network server 101 a / 101 b / 101 n and is accessible and executable by the processor 206 . In either embodiment, the privacy settings differentiator engine 306 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a / 101 b / 101 n via signal line 226 .
  • the privacy settings differentiator engine 306 also determines equivalent privacy settings among the first set of privacy settings and second set of privacy settings, wherein the equivalent privacy settings are further compared to determine whether different privacy settings levels exist. For example, a privacy setting in one social network may be called “visibility” while an equivalent privacy setting in a second social network may be called “exposure.” The privacy settings differentiator engine 306 determines that these two settings are equivalent and compares the two for differences.
  • the privacy settings differentiator engine 306 compares the user's privacy settings of the first social network 101 a to the user's privacy settings of the at least one other social network 101 b , 101 n until it detects a first difference then stops comparing and detecting. In another embodiment, the privacy settings differentiator engine 306 compares all the user's privacy settings of the first social network 101 a to all the user's privacy settings of the at least one other social network 101 b , 101 n and detects all the differences. In one embodiment, a difference exists, or the privacy settings differ, when the privacy setting of the first social network 101 a is less restrictive than the privacy setting of the at least one other social network 101 b , 101 n . In such an embodiment, the privacy settings differentiator engine 306 detects differences where the user's first social network's 101 a privacy settings are less restrictive than the user's privacy settings of the at least one other social network 101 b , 101 n.
  • the differentiation display engine 308 is software and routines executable by the processor for notifying the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b , 101 n and sending that notification for display to the user.
  • the differentiation display engine 308 is a set of instructions executable by the processor 206 to provide the functionality described below for generating a notification when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b , 101 n and sending that notification for display to the user.
  • the differentiation display engine 308 is stored in the memory 208 of the social network server 101 a / 101 b / 101 n and is accessible and executable by the processor 206 . In either embodiment, the differentiation display engine 308 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a / 101 b / 101 n via signal line 228 .
  • the notification is a pop-up window. In one embodiment the notification is a banner. In another embodiment, the notification is an e-mail or message to the user. In one embodiment, the notification appears on the page where privacy settings are normally set or displayed. In another embodiment, the notification is another webpage. Other embodiments may use other forms of notification.
  • the differentiation display engine 308 receives the results of the privacy settings differentiator engine 306 , generates a notification based on those results, and sends that notification for display to the user. In one embodiment, when no difference is detected by the privacy settings differentiator engine 306 , no notification is generated or sent for display to the user. In another embodiment, when no difference is detected, a notification is generated and sent to the user to notify the user that no difference was detected.
  • the differentiation display engine 308 when one or more differences are detected by the privacy settings differentiator engine 306 , the differentiation display engine 308 generates a notification and sends the notification for display to the user.
  • the generated notification notifies the user that one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n . For example, “Warning! This social network has different privacy settings than your other social network.”
  • the generated notification notifies the user that one or more of the user's privacy settings of the first social network 101 a are less restrictive than the user's privacy settings of at least one other social network 101 b , 101 n . For example, “Warning! This social network has less restrictive privacy settings than your other social network; therefore, you may be sharing more information on this social network than you desire.”
  • the generated notification includes information about which user privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b , 101 n . For example, “Warning! This social network has different privacy settings for photographs than your other social network.” In one embodiment, the generated notification includes information about which user privacy settings of the first social network 101 a are less restrictive than the user's privacy settings of the at least one or more other social network 101 b , 101 n . For example, “Warning! This social network has less restrictive privacy settings for posts than your other social network; therefore, you may be sharing your posts on this social network with more users than you desire.”
  • the generated notification identifies the at least one other social network 101 b , 101 n that has privacy settings that differ from the user's privacy settings of the first social network 101 a . For example, “Warning! This social network has different privacy settings than your Orkut account.” In one embodiment, the generated notification identifies the at least one other social network 101 b , 101 n that have more restrictive privacy settings than the user's privacy settings of the first social network 101 a . For example, “Warning! This social network has less restrictive privacy settings than your Orkut profile.”
  • the generated notification includes, for one or more of the privacy settings that differ, what the user's privacy settings of the first social network 101 a and of the at least one other social network 101 b , 101 n are. For example, “Warning! Photographs on this social network are viewable by the public, while your photographs on Orkut are viewable only by your friends.”
  • the notification gives the user the option to view the user's privacy settings of the user's first social network 101 a .
  • the notification requests that the user confirm receipt of the notification in order for the notification to close, e.g., by clicking on a button.
  • the notification gives the user the option to adjust the user's privacy settings of the user's first social network 101 a.
  • the privacy settings adjustment engine 310 is software and routines executable by the processor for adjusting one or more of the user's privacy settings of the first social network 101 a .
  • the privacy settings adjustment engine 310 is a set of instructions executable by the processor 206 to provide the functionality described below for adjusting one or more of the user's privacy settings of the first social network 101 a .
  • the privacy settings adjustment engine 310 is stored in the memory 208 of the social network server 101 a / 101 b / 101 n and is accessible and executable by the processor 206 .
  • the privacy settings adjustment engine 310 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a / 101 b / 101 n via signal line 230 .
  • the privacy settings adjustment engine 310 receives the user's request to adjust one or more privacy settings of the first social network 101 a and links the user to the social network 101 a page where privacy settings are normally adjusted. In one embodiment, the privacy settings adjustment engine 310 receives the user's request to adjust one or more privacy settings of the first social network 101 a and updates the user's privacy settings in the storage device and/or data storage device 110 a . In one embodiment, after the user adjusts one or more privacy settings of the first social network 101 a , a request to notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n is sent.
  • FIG. 5 illustrates an example of a storage device 214 storing user data 500 including data belonging to User-A 510 a according to one embodiment.
  • the User-A data 510 a includes data regarding the user's profile 520 a , the user's privacy settings 520 b , and other data 520 n .
  • the user's privacy settings data 520 b includes the privacy settings for the user's biographic information 530 a , posts 530 b , photos 530 c , and other privacy settings data 530 n.
  • FIG. 4 a flow chart illustrating an embodiment of a method 400 for notifying a first social network user when one or more the user's privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b , 101 n is shown.
  • the request receiver engine 302 of the differentiation detection module 220 a receives 402 a request to notify the first social network user when one or more the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n .
  • the request received 402 is a login request.
  • the request received 402 is a request to edit the user's privacy settings of the first social network 101 a .
  • the request received 402 is the user selecting a button or hypertext link for requesting a notification when one or more the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n.
  • the privacy settings retrieval engine 304 of the differentiation detection module 220 a receives 404 the privacy settings from the user's first social network 101 a and the user's privacy settings from at least one other social network 101 b , 101 n .
  • the data is received 404 from the storage device 214 of one or more of the social network servers 101 a , 101 b , 101 n .
  • the data is received from the data storage 110 a / 110 b / 110 n of one or more of the social network servers 101 a , 101 b , 101 n.
  • the privacy settings differentiator engine 306 of the differentiation detection module 220 a receives the privacy settings received by the privacy settings retrieval engine 304 then compares 406 the user's privacy settings on the first social network 101 a to the user's privacy settings of the at least one other social network 101 b , 101 n and detects 408 one or more differences.
  • the privacy settings differentiator engine 306 also determines equivalent privacy settings among the first set of privacy settings and second set of privacy settings, wherein the equivalent privacy settings are further compared to determine whether different privacy settings levels exist. For example, a privacy setting in one social network may be called “visibility” while an equivalent privacy setting in a second social network may be called “exposure.” The privacy settings differentiator engine 306 determines that these two settings are equivalent and compares the two for differences.
  • the privacy settings differentiator engine 306 compares the user's privacy settings on the first social network 101 a to the user's privacy settings of the at least one other social network 101 b , 101 n until it detects 408 a first difference then stops comparing 406 and detecting 408 .
  • the privacy settings differentiator engine 306 compares 406 all the user's privacy settings on the first social network 101 a to all the user's privacy settings of the at least one other social network 101 b , 101 n and detects 408 all the differences.
  • the privacy settings differentiator engine 306 detects 408 a difference only when the first social network's 101 a privacy setting is less restrictive than the privacy setting of the at least one other social network 101 b , 101 n.
  • the differentiation display engine 308 of the differentiation detection module 220 a generates 412 a notification based on any differences detected 408 by the privacy settings differentiator engine 306 and sends 414 the notification for display to the user.
  • no notification is generated or sent for display to the user.
  • a notification is generated and sent to the user to notify the user that no differences were detected (not shown).
  • the differentiation display engine 308 when one or more differences are detected ( 410 —Yes), the differentiation display engine 308 generates ( 412 ) a notification and sends ( 410 ) the notification for display to the user.
  • the generated 412 notification notifies the user when one or more of the user's privacy settings on the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n .
  • the generated 412 notification includes information about which of the user's privacy settings on the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b , 101 n .
  • the generated 412 notification identifies the at least one other social network 101 b , 101 n that has privacy settings that differ from those on the first social network 101 a . In one embodiment, the generated 412 notification includes, for one or more of the privacy settings that differ, what the privacy settings are set to on the first social network 101 a and the at least one other social network 101 b , 101 n.
  • the notification gives the user the option to view the user's privacy settings of the user's first social network 101 a by including a link to privacy settings page.
  • the notification gives the user the option to change the user's privacy settings fn the user's first social network 101 a by including a link to a privacy settings editing page (see FIG. 6 ).
  • the notification gives the user the option to adjust the privacy settings of the first social network in the notification (not shown).
  • the notification requires user to confirm receipt of the notification in order for the notification to close (see FIG. 6 ).
  • the notification may appear in any number of places including, but not limited to, an e-mail, a pop-up, a banner, a separate webpage, or where the privacy settings are typically set or displayed.
  • FIG. 6 is a graphic representation of an example of a user interface 600 displaying a user's social networking page 602 .
  • the notification 604 appears in a pop-up window 606 .
  • the notification 604 notifies the first social network user that the user's first social network uses less restrictive privacy settings than the user's other social network 101 b / 101 n ; however, as previously discussed, the notification 604 can contain different/other information.
  • the notification requires user to confirm the receipt of the notification 604 by using the user input device 608 to select a confirmation button 610 .
  • the notification 604 gives the user the option to edit the user's privacy settings by linking them to the privacy settings edit page, which is accomplished by the “Edit” button 612 in the illustrated embodiment.
  • FIG. 7 is a graphic representation of a user interface 700 displaying a notification 703 on a separate social networking page 702 .
  • the notification 703 notifies the user that the first social network's 101 a privacy settings differ from those on one or more of the user's other social networks 101 b , 101 n .
  • the notification 703 can include information about which privacy settings differ and what those settings are.
  • table 704 includes information about which privacy settings differ and what each of those settings is.
  • Table 704 includes column 706 , which contains the one or more features associated with privacy settings that differ between the user's first social network 101 a and at least one other social network 101 b , 101 n according to one embodiment.
  • Table 704 includes column 708 , which contains the first social network's 101 a privacy settings associated with each of the one or more features in column 706 .
  • Table 704 includes column 710 , which contains the privacy settings associated with each of the one or more features in column 706 in a first different social network 101 b / 101 n to which the user also belongs.
  • Table 704 includes column 712 , which contains the privacy settings associated with each of the one or more features in column 706 in a second different social network 101 b / 101 n to which the user also belongs.
  • the user is notified which privacy settings are different and how those settings are different by reading across a row in table 704 .
  • row 705 notifies the user that the privacy setting for the user's “First/Last Name” varies because the user's first social network has a privacy setting that makes that data and information public, “Other Social Network 1” has a different setting, and “Other Social Network 2's” privacy setting matches that of the first social network in one embodiment.
  • box 714 is left empty. In one embodiment, a box is left empty when the privacy setting for that feature on that social network matches the privacy setting for that feature on the user's first social network.
  • modules, routines, features, attributes, methodologies and other aspects of the embodiments can be implemented as software, hardware, firmware or any combination of the three.
  • a component an example of which is a module
  • the component can be implemented as software
  • the component can be implemented as a standalone program, as part of a larger program, as a plurality of separate programs, as a statically or dynamically linked library, as a kernel loadable module, as a device driver, and/or in every and any other way known now or in the future to those of ordinary skill in the art of computer programming.
  • the embodiments are in no way limited to implementation in any specific programming language, or for any specific operating system or environment. Accordingly, the disclosure is intended to be illustrative, but not limiting, of the scope, which is set forth in the following claims.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Hardware Design (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Bioethics (AREA)
  • Computing Systems (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Business, Economics & Management (AREA)
  • Signal Processing (AREA)
  • Software Systems (AREA)
  • Marketing (AREA)
  • Primary Health Care (AREA)
  • Strategic Management (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Medical Informatics (AREA)
  • Databases & Information Systems (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

A system and method for generating a notification of privacy settings difference is disclosed. A request is received. A first set of privacy settings is received from a first social network, and a second set of privacy settings is received from at least one other social network. The first set of is compared to the second set. A difference between the first set and the second is detected, and a notification is generated. The notification includes an indication that a difference was detected. The notification is sent for display to the user. In one embodiment, the notification allows the user to request to view, or edit, the first set of privacy settings. In one embodiment, the notification sends the user to a webpage on the first social network where the first set is typically displayed and/or edited. In another embodiment, the notification displays the first set and/or receives the edits.

Description

CROSS REFERENCE TO RELATED APPLICATIONS
This application is a continuation of and claims priority under 35 USC §119(e) to U.S. application Ser. No. 13/173,359, entitled “System and Method for Privacy Setting Differentiation Detection,” filed on Jun. 30, 2011, the entirety of which is herein incorporated by reference.
The specification relates to social networks. In particular, the present specification relates to privacy settings on social networks. The present specification also relates to generating and sending a notification to a first social network user when the user's privacy settings of the first social network differ from the user's privacy settings in at least one other social network.
BACKGROUND
Social networks are becoming an increasingly popular way for people to stay connected. This increasing popularity of social networks has given rise to social network services that have developed various ways users of the social network can communicate and share information. Users within a social network can send each other messages, view other users' activities and share personal information, including personal photographs and videos. Social networking services can provide a forum for users to remain in close contact despite geographic distance or uncoordinated schedules. Social network users are typically able to adjust the amount and type of information they choose to share and how and with whom that information is shared. However, for users belonging to multiple social networks, it may be difficult for the users to monitor the privacy settings of each social network, remember the different privacy settings of each social network, or even realize that each social network's privacy settings are different.
SUMMARY OF THE INVENTION
The deficiencies and limitations of the prior art at least in part are overcome by providing a system and method for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings in at least one other social network.
A system and method are provided for generating a notification of privacy settings difference. In one embodiment the system includes a request receiver engine, privacy settings retrieval engine, privacy settings differentiator engine, differentiation display engine and an optional privacy settings adjustment engine. The request receiver engine for receives a request. The privacy settings retrieval engine receives a first set of privacy settings of a user from a first social network and a second set of privacy settings of the user from at least one other social network. The privacy settings differentiator engine compares the privacy settings of the first social network to those of the of the at least one other social network and, responsive to detecting a difference between the first set of privacy settings and the second set of privacy settings, prompts the differentiation display engine to generate a notification. The notification is sent to the user for display and includes an indication that the difference has been detected.
In one embodiment, the request is the user's login request that is sent to the first social network. In another embodiment, the request is the user's request to edit one or more privacy settings of the first social network. In yet another embodiment, the request is the user selecting a button or hypertext link on the first social network. In one embodiment, the difference exists when the privacy setting of the first set of privacy settings is less restrictive than the privacy setting of the second set of privacy settings.
The notification may include a variety of information and features. In one embodiment, the notification identifies at least one other social network having the detected difference from the first social network. In another embodiment, the notification includes the detected difference between the first set of privacy settings and the second set of privacy settings. In one embodiment, the notification allows the user to request to view, or edit, one or more of the privacy settings of the first social network. In one such embodiment, the privacy settings adjustment engine receives the user's request to view, or edit, the privacy settings of the first social network; and sends the user to a webpage on the first social network where the privacy settings are typically displayed, or edited. In another such embodiment, the privacy settings adjustment module receives the user's request to edit and one or more edits to the user's privacy settings of the first social network; and updates the privacy settings of the first social network according to the edits received from the user.
BRIEF DESCRIPTION OF THE DRAWINGS
The embodiments are illustrated by way of example, and not by way of limitation in the figures of the accompanying drawings in which like reference numerals are used to refer to similar elements.
FIG. 1 illustrates a block diagram of a system for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings in at least one other social network according to one embodiment.
FIG. 2 is a block diagram of a social network server in accordance with one embodiment.
FIG. 3 is a block diagram illustrating a differentiation detection module according to one embodiment.
FIG. 4 is a flow chart illustrating a method for detecting and notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network according to one embodiment.
FIG. 5 illustrates a storage device storing user data including the user's privacy settings according to one embodiment.
FIG. 6 is a graphic representation of an example of a user interface displaying a notification to the first social network user that one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network according to one embodiment.
FIG. 7 is a graphic representation of another example of a user interface displaying a notification to the first social network user that one or more of the user's privacy settings differ from the user's privacy settings on at least one other social network according to another embodiment.
DETAILED DESCRIPTION
A system and method for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network is described. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments. It will be apparent, however, to one skilled in the art that the embodiments can be practiced without these specific details. In other instances, structures and devices are shown in block diagram form in order to avoid obscuring the embodiments. For example, the present embodiments are described in one embodiment below with reference to user interfaces and particular hardware. However, the present embodiments apply to any type of computing device that can receive data and commands, and any peripheral devices providing services.
Reference in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
Some portions of the detailed descriptions that follow are presented in terms of algorithms and symbolic representations of operations on data bits within a computer memory. These algorithmic descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self consistent sequence of steps leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers or the like.
It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussion, it is appreciated that throughout the description, discussions utilizing terms such as “processing” or “computing” or “calculating” or “determining” or “displaying” or “comparing” or identifying” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.
The present embodiments also relate to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic disks, read-only memories (ROMs), random access memories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, flash memories including USB keys with non-volatile memory or any type of media suitable for storing electronic instructions, each coupled to a computer system bus.
The embodiments can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements. A preferred embodiment is implemented in software, which includes but is not limited to firmware, resident software, microcode, etc.
Furthermore, one embodiment can take the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by or in connection with a computer or any instruction execution system. For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
A data processing system suitable for storing and/or executing program code will include at least one processor coupled directly or indirectly to memory elements through a system bus. The memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memories which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution.
Input/output or I/O devices (including but not limited to keyboards, displays, pointing devices, etc.) can be coupled to the system either directly or through intervening I/O controllers.
Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.
Finally, the algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Various general-purpose systems may be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform the required method steps. The required structure for a variety of these systems will appear from the description below. In addition, the present embodiments are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the embodiments as described herein.
System Overview
FIG. 1 illustrates a block diagram of a system 100 for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings on at least one other social network according to one embodiment. The illustrated embodiment of the system 100 for notifying a first social network user when one or more of the user's privacy settings differ from the user's privacy settings on at least one other social network includes user devices 115 a, 115 b, 115 n that are accessed by users 125 a, 125 b, 125 n and a third party server 107. The system 100 also includes social network servers 101 a, 101 b, 101 n. In the illustrated embodiment, these entities are communicatively coupled via a network 105. Although only three devices are illustrated, persons of ordinary skill in the art will recognize that any number of user devices 115 n are available to any number of users 125 n. Further, although only three servers 101 a, 101 b, 101 n are illustrated, persons of ordinary skill in the art will recognize that any number of social network servers 101 n are available.
The user devices 115 a, 115 b, 115 n and social network servers 101 a, 101 b, 101 n in FIG. 1 are used by way of example. While FIG. 1 illustrates three devices, the present embodiment applies to any system architecture having one or more user devices and one or more social network servers associated with two or more social networks. Furthermore, while only one network 105 is coupled to the user devices, 115 a, 115 b, 115 n, the social network servers 101 a, 101 b, 101 n, and the third party server 107, in practice any number of networks 105 can be connected to the entities. Furthermore, while only one third party application server 107 is shown, the system 100 could include one or more third party application servers 107.
In one embodiment, the social network server 101 a/101 b/101 n also contains a social network module 209. A social network is any type of social structure where the users are connected by a common feature. Examples include, but are not limited to, Orkut, Buzz, blogs, microblogs, and Internet forums. The common feature includes friendship, family, a common interest, etc. The common feature includes friendship, family, work, an interest, etc. Although a person of ordinary skill in the art will recognize that a social network can comprise one or more social network servers 101 a, 101 b, 101 n, for the purposes of describing the components and functionality of the system 100, the below description describes the system 100 where each social network server 101 a/101 b/101 n belongs to and represents a different social network.
The network 105 enables communications between the user devices 115 a, 115 b, 115 n, the social network servers 101 a, 101 b, 101 n, and the third party application server 107. Thus, the network 105 can include links using technologies such as Wi-Fi, Wi-Max, 2G, Universal Mobile Telecommunications System (UMTS), 3G, Ethernet, 802.11, integrated services digital network (ISDN), digital subscriber line (DSL), asynchronous transfer mode (ATM), InfiniBand, PCI Express Advanced Switching, etc. Similarly, the networking protocols used on the network 105 can include the transmission control protocol/Internet protocol (TCP/IP), multi-protocol label switching (MPLS), the User Datagram Protocol (UDP), the hypertext transport protocol (HTTP), the simple mail transfer protocol (SMTP), the file transfer protocol (FTP), lightweight directory access protocol (LDAP), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Global System for Mobile communications (GSM), High-Speed Downlink Packet Access (HSDPA), etc. The data exchanged over the network 105 can be represented using technologies and/or formats including the hypertext markup language (HTML), the extensible markup language (XML), etc. In addition, all or some of links can be encrypted using conventional encryption technologies such as the secure sockets layer (SSL), Secure HTTP and/or virtual private networks (VPNs) or Internet Protocol security (IPsec). In another embodiment, the entities can use custom and/or dedicated data communications technologies instead of, or in addition to, the ones described above. Depending upon the embodiment, the network 105 can also include links to other networks.
In one embodiment, the network 105 is a partially public or a wholly public network such as the Internet. The network 105 can also be a private network or include one or more distinct or logical private networks (e.g., virtual private networks, Wide Area Networks (“WAN”) and/or Local Area Networks (“LAN”)). Additionally, the communication links to and from the network 105 can be wireline or wireless (i.e., terrestrial—or satellite-based transceivers). In one embodiment, the network 105 is an IP-based wide or metropolitan area network.
In some embodiments, the network 105 helps to form a set of online relationships between users 125 a, 125 b, 125 n, such as provided by one or more social networking systems including explicitly-defined relationships and relationships implied by social connections with other online users, where the relationships form a social graph. In some examples, the social graph can reflect a mapping of these users and how they are related.
In one embodiment, a differentiation detection module 220 a is included in the social network server 101 a/101 b/101 n and is operable on the social network server 101 a/101 b/101 n. In another embodiment, the differentiation detection module 220 b is included in the third party application server 107 and is operable on the third party application server 107. Persons of ordinary skill in the art will recognize that the differentiation detection module 220 a/220 b can be stored in any combination on the devices and servers. In some embodiments the differentiation detection module 220 a/220 b includes multiple, distributed modules that cooperate with each other to perform the functions described below. Details describing the functionality and components of the differentiation detection module 220 a of the social network server 101 a/101 b/101 n are explained in further detail below with regard to FIG. 3.
In the illustrated embodiment, the user devices 115 a, 115 b are coupled to the network 105 via signal lines 108 and 112, respectively. The user 125 a is communicatively coupled to the user device 115 a via signal line 116. Similarly, the user 125 b is communicatively coupled to the user device 115 b via signal line 114. The third party application 107 is communicatively coupled to the network 105 via signal line 106. The social network servers 101 a, 101 b, are coupled to the network 105 via signal lines 132, 134, respectively. In one embodiment, the social network servers 101 a, 101 b are each communicatively coupled to a data storage device 110 a/110 b via a signal line 142/144, respectively.
In one embodiment, data storage 110 a/110 b/110 n stores data and information of users 125 a, 125 b, 125 n of the social network 101 a/101 b/101 n. Such stored information includes user profiles and other information identifying each user 125 a/125 b/125 n of the social network 101 a/101 b/101 n. Examples of information identifying users includes, but is not limited to, the user's name, contact information, sex, relationship status, likes, interests, links, education and employment history, location, political views, and religion. In one embodiment, the information stored in data storage 110 a/110 b/110 n also includes the user's list of current and past friends and the user's activities within the social network 101 a/101 b/101 n, such as anything the user posts within the social network 101 a/101 b/101 n and any messages that the user sends to other social network 101 a/101 b/101 n users. In one embodiment, the data and information stored by the data storage 110 a/110 b/110 n includes the user's 125 a/125 b/125 n privacy settings. In another embodiment, which is discussed below, a storage device 214 (see FIG. 2) is included in the social network server 101 a/101 b/101 n and the storage device 214 stores the data and information of the users 125 a, 125 b, 125 n of the social network 101 a/101 b/101 n discussed in relation to the data storage 110 a/110 b/110 n.
In one embodiment, the user device 115 a, 115 b, 115 n is an electronic device having a web browser for interacting with one or more social network servers 101 a, 101 b, 101 n via the network 105 and is used by user 125 a, 125 b, 125 n to access information in the system 100. The user device 115 a, 115 b, 115 n can be, for example, a laptop computer, a desktop computer, a tablet computer, a mobile telephone, a personal digital assistant (PDA), a mobile email device, a portable game player, a portable music player, a portable music player, or any other electronic device capable of accessing a network.
Social Network Server 101 a/101 b/101 n
FIG. 2 is a block diagram of an embodiment of a social network server 101 a/101 b/101 n. As illustrated in FIG. 2, the social network server 101 a/101 b/101 n includes a network adapter 202 coupled to a bus 204. According to one embodiment, also coupled to the bus 204 are at least one processor 206, memory 208, a social network module 209, a graphics adapter 210, an input device 212, a storage device 214, and a differentiation detection module 220 a. In one embodiment, the functionality of the bus 204 is provided by an interconnecting chipset. In one embodiment, the social network server 101 a/101 b/101 n also includes a display 218, which is coupled to the graphics adapter 210.
The processor 206 may be any general-purpose processor. The processor 206 comprises an arithmetic logic unit, a microprocessor, a general purpose controller or some other processor array to perform computations, provide electronic display signals to display 218. The processor 206 is coupled to the bus 204 for communication with the other components of the social network server 101 a/101 b/101 n. Processor 206 processes data signals and may comprise various computing architectures including a complex instruction set computer (CISC) architecture, a reduced instruction set computer (RISC) architecture, or an architecture implementing a combination of instruction sets. Although only a single processor is shown in FIG. 2, multiple processors may be included. The social network server 101 a/101 b/101 n also includes an operating system executable by the processor such as but not limited to WINDOWS®, MacOS X, Android, or UNIX® based operating systems.
The memory 208 holds instructions and data used by the processor 206. The instructions and/or data comprise code for performing any and/or all of the techniques described herein. The memory 208 may be a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, flash memory or some other memory device known in the art. In one embodiment, the memory 208 also includes a non-volatile memory such as a hard disk drive or flash drive for storing log information on a more permanent basis. The memory 208 is coupled by the bus 204 for communication with the other components of the social network server 101 a/101 b/101 n. In one embodiment, the differentiation detection module 220 a is stored in memory 208 and executable by the processor 206.
In one embodiment, the social network module 209 is software and routines executable by the processor 206 to control the interaction between the social network server 101 a/101 b/101 n, storage device 214 and the user devices 115 a, 115 b, 115 n. An embodiment of the social network module 209 allows users 125 a, 125 b, 125 n of user devices 115 a, 115 b, 115 n to perform social functions between other users 125 a, 125 b, 125 n of user devices 115 a, 115 b, 115 n within the system 100.
The storage device 214 is any device capable of holding data, like a hard drive, compact disk read-only memory (CD-ROM), DVD, or a solid-state memory device. The storage device 214 is a non-volatile memory device or similar permanent storage device and media. The storage device 214 stores data and instructions for processor 208 and comprises one or more devices including a hard disk drive, a floppy disk drive, a CD-ROM device, a DVD-ROM device, a DVD-RAM device, a DVD-RW device, a flash memory device, or some other mass storage device known in the art. In one embodiment, the storage device 214 is used to store user profiles and other information identifying users 125 a, 125 b, 125 n of the social network 101 a/101 b/101 n. In some embodiments, such user data is stored in data storage 110 a/110 b/110 n.
The input device 212 may include a mouse, track ball, or other type of pointing device to input data into the social network server 101 a. The input device 212 may also include a keyboard, such as a QWERTY keyboard. The input device 212 may also include a microphone, a web camera or similar audio or video capture device. The graphics adapter 210 displays images and other information on the display 218. The display 218 is a conventional type such as a liquid crystal display (LCD) or any other similarly equipped display device, screen, or monitor. The display 218 represents any device equipped to display electronic images and data as described herein. The network adapter 202 couples the social network server 101 a/101 b/101 n to a local or wide area network.
The differentiation detection module 220 a is software and routines executable by the processor 206 to notify a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network. Details describing the functionality and components of the differentiation detection module 220 a are explained in further detail below with regard to FIG. 3.
As is known in the art, a social network server 101 a/101 b/101 n can have different and/or other components than those shown in FIG. 2. In addition, the social network server 101 a can lack certain illustrated components. In one embodiment, a social network server 101 a/101 b/101 n lacks an input device 212, graphics adapter 210, and/or display 218. Moreover, the storage device 214 can be local and/or remote from the social network server 101 a/101 b/101 n (such as embodied within a storage area network (SAN)).
As is known in the art, the social network server 101 a/101 b/101 n is adapted to execute computer program modules for providing functionality described herein. As used herein, the term “module” refers to computer program logic utilized to provide the specified functionality. Thus, a module can be implemented in hardware, firmware, and/or software. In one embodiment, program modules are stored on the storage device 214, loaded into the memory 208, and executed by the processor 206.
Embodiments of the entities described herein can include other and/or different modules than the ones described here. In addition, the functionality attributed to the modules can be performed by other or different modules in other embodiments. Moreover, this description occasionally omits the term “module” for purposes of clarity and convenience.
Differentiation Detection Module 220 a
Referring now to FIG. 3, the differentiation detection module 220 a is shown in more detail. FIG. 3 is a block diagram of a portion of the social network server 101 a/101 b/101 n that includes the differentiation detection module 220 a, a processor 206 and a memory 208, along with other modules and components recited in the description of FIG. 2. In one embodiment, the third party application server 107 includes the differentiation detection module 220 b. In one embodiment, the differentiation detection module 220 a is software and routines executable by the processor 206 to notify a first social network user when one or more of the user's privacy settings differ from the user's privacy settings of at least one other social network. For the purposes of describing the components and functionality of the differentiation detection module 220 a/220 b, the below description describes the differentiation detection module 220 a. However, one of ordinary skill in the art will appreciate that the same description is also applicable to the functionality and components of the differentiation detection module 220 b. Also for the purposes of describing the components and functionality of the differentiation detection module 220 a, the below description describes the differentiating behavior authentication module 220 a where the user's first social network is represented by social network server 101 a and each social network server 101 a, 101 b, and 101 n represents a different social network. However, one of ordinary skill in the art will appreciate that the same description is also applicable to the functionality and components of the differentiation detection module 220 a of 110 b, 110 n and 107 as long as one or more social network servers associated with two or more social networks are present.
In one embodiment, the differentiation detection module 220 a comprises a request receiver engine 302, a privacy settings retrieval engine 304, a privacy settings differentiator engine 306, and a differentiation display engine 308. In one embodiment, the differentiation detection module also includes an optional privacy settings adjustment engine 310.
The request receiver engine 302 is software and routines executable by the processor for receiving a request for access to information on a social network, wherein the information includes privacy settings information of a user and notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. In one embodiment, the request receiver engine 302 is a set of instructions executable by the processor 206 to provide the functionality described below for receiving a request for access to information on a social network, wherein the information includes privacy settings information of a user and notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. In another embodiment, the request receiver engine 302 is stored in the memory 208 of the social network server 101 a/101 b/101 n and is accessible and executable by the processor 206. In either embodiment, the request receiver engine 302 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a/101 b/101 n via signal line 222.
In one embodiment, the request received by the request receiver engine 302 to notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n is the user's login request, i.e., the user, by logging into the first social network 101 a, automatically requests to be notified when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. In one embodiment, the user's request to edit the user's privacy settings of the first social network 101 a is the request received by the request receiver 302, i.e., the user, by changing one or more privacy settings of the first social network, automatically requests to be notified when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. In one embodiment, the user can request to be notified when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n by clicking on a button or hypertext link, which is received by the request receiver engine 302.
The privacy settings retrieval engine 304 is software and routines executable by the processor for receiving the user's privacy settings data from the first social network 101 a and from at least one other social network 101 b, 101 n to which the user belongs and sending that data to the privacy settings differentiator engine 306. In one embodiment, the privacy settings retrieval engine 304 is a set of instructions executable by the processor 206 to provide the functionality described below for receiving the user's privacy settings data from the first social network 101 a and from at least one other social network 101 b, 101 n to which the user belongs and sending that data to the privacy settings differentiator engine 306. In another embodiment, the privacy settings retrieval engine 304 is stored in the memory 208 of the social network server 101 a/101 b/101 n and is accessible and executable by the processor 206. In either embodiment, the privacy settings retrieval engine 304 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a/101 b/101 n via signal line 224.
The privacy settings retrieval engine 304 is also communicatively coupled, via the differentiation detection module 220 a of the each social network server 101 a/101 b/101 n to other social network servers 101 a, 101 b, 101 n. In one embodiment, the privacy settings retrieval engine 304 receives the user's privacy settings data from the storage device of one or more social networks 101 a, 101 b, 101 n to which the user belongs. In one embodiment, the privacy settings retrieval engine 304 receives the user's privacy settings data associated with one or more social networks 101 a, 101 b, 101 n to which the user belongs.
The privacy settings differentiator engine 306 is software and routines executable by the processor for receiving the privacy settings data received by the privacy settings retrieval engine 304, comparing the privacy settings of the first social network 101 a and the privacy settings of at least one other social network 101 b, 101 n, and detecting differences. In one embodiment, the privacy settings differentiator engine 306 is a set of instructions executable by the processor 206 to provide the functionality described below for receiving the privacy settings received by the privacy settings retrieval engine 304, comparing the privacy settings of the first social network 101 a and privacy settings of the at least one other social network 101 b, 101 n, and detecting differences. In another embodiment, the privacy settings differentiator engine 306 is stored in the memory 208 of the social network server 101 a/101 b/101 n and is accessible and executable by the processor 206. In either embodiment, the privacy settings differentiator engine 306 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a/101 b/101 n via signal line 226.
In one embodiment, the privacy settings differentiator engine 306 also determines equivalent privacy settings among the first set of privacy settings and second set of privacy settings, wherein the equivalent privacy settings are further compared to determine whether different privacy settings levels exist. For example, a privacy setting in one social network may be called “visibility” while an equivalent privacy setting in a second social network may be called “exposure.” The privacy settings differentiator engine 306 determines that these two settings are equivalent and compares the two for differences.
In one embodiment, the privacy settings differentiator engine 306 compares the user's privacy settings of the first social network 101 a to the user's privacy settings of the at least one other social network 101 b, 101 n until it detects a first difference then stops comparing and detecting. In another embodiment, the privacy settings differentiator engine 306 compares all the user's privacy settings of the first social network 101 a to all the user's privacy settings of the at least one other social network 101 b, 101 n and detects all the differences. In one embodiment, a difference exists, or the privacy settings differ, when the privacy setting of the first social network 101 a is less restrictive than the privacy setting of the at least one other social network 101 b, 101 n. In such an embodiment, the privacy settings differentiator engine 306 detects differences where the user's first social network's 101 a privacy settings are less restrictive than the user's privacy settings of the at least one other social network 101 b, 101 n.
The differentiation display engine 308 is software and routines executable by the processor for notifying the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b, 101 n and sending that notification for display to the user. In one embodiment, the differentiation display engine 308 is a set of instructions executable by the processor 206 to provide the functionality described below for generating a notification when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b, 101 n and sending that notification for display to the user. In another embodiment, the differentiation display engine 308 is stored in the memory 208 of the social network server 101 a/101 b/101 n and is accessible and executable by the processor 206. In either embodiment, the differentiation display engine 308 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a/101 b/101 n via signal line 228.
In one embodiment, the notification is a pop-up window. In one embodiment the notification is a banner. In another embodiment, the notification is an e-mail or message to the user. In one embodiment, the notification appears on the page where privacy settings are normally set or displayed. In another embodiment, the notification is another webpage. Other embodiments may use other forms of notification.
In one embodiment, the differentiation display engine 308 receives the results of the privacy settings differentiator engine 306, generates a notification based on those results, and sends that notification for display to the user. In one embodiment, when no difference is detected by the privacy settings differentiator engine 306, no notification is generated or sent for display to the user. In another embodiment, when no difference is detected, a notification is generated and sent to the user to notify the user that no difference was detected.
In one embodiment, when one or more differences are detected by the privacy settings differentiator engine 306, the differentiation display engine 308 generates a notification and sends the notification for display to the user. In one embodiment, the generated notification notifies the user that one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. For example, “Warning! This social network has different privacy settings than your other social network.” In one embodiment, the generated notification notifies the user that one or more of the user's privacy settings of the first social network 101 a are less restrictive than the user's privacy settings of at least one other social network 101 b, 101 n. For example, “Warning! This social network has less restrictive privacy settings than your other social network; therefore, you may be sharing more information on this social network than you desire.”
In one embodiment, the generated notification includes information about which user privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b, 101 n. For example, “Warning! This social network has different privacy settings for photographs than your other social network.” In one embodiment, the generated notification includes information about which user privacy settings of the first social network 101 a are less restrictive than the user's privacy settings of the at least one or more other social network 101 b, 101 n. For example, “Warning! This social network has less restrictive privacy settings for posts than your other social network; therefore, you may be sharing your posts on this social network with more users than you desire.”
In one embodiment, the generated notification identifies the at least one other social network 101 b, 101 n that has privacy settings that differ from the user's privacy settings of the first social network 101 a. For example, “Warning! This social network has different privacy settings than your Orkut account.” In one embodiment, the generated notification identifies the at least one other social network 101 b, 101 n that have more restrictive privacy settings than the user's privacy settings of the first social network 101 a. For example, “Warning! This social network has less restrictive privacy settings than your Orkut profile.”
In one embodiment, the generated notification includes, for one or more of the privacy settings that differ, what the user's privacy settings of the first social network 101 a and of the at least one other social network 101 b, 101 n are. For example, “Warning! Photographs on this social network are viewable by the public, while your photographs on Orkut are viewable only by your friends.” In one embodiment, the notification gives the user the option to view the user's privacy settings of the user's first social network 101 a. In one embodiment, the notification requests that the user confirm receipt of the notification in order for the notification to close, e.g., by clicking on a button. In one embodiment, the notification gives the user the option to adjust the user's privacy settings of the user's first social network 101 a.
The privacy settings adjustment engine 310 is software and routines executable by the processor for adjusting one or more of the user's privacy settings of the first social network 101 a. In one embodiment, the privacy settings adjustment engine 310 is a set of instructions executable by the processor 206 to provide the functionality described below for adjusting one or more of the user's privacy settings of the first social network 101 a. In another embodiment, the privacy settings adjustment engine 310 is stored in the memory 208 of the social network server 101 a/101 b/101 n and is accessible and executable by the processor 206. In either embodiment, the privacy settings adjustment engine 310 is adapted for cooperation and communication with the processor 206 and other components of the social network server 101 a/101 b/101 n via signal line 230.
In one embodiment, the privacy settings adjustment engine 310 receives the user's request to adjust one or more privacy settings of the first social network 101 a and links the user to the social network 101 a page where privacy settings are normally adjusted. In one embodiment, the privacy settings adjustment engine 310 receives the user's request to adjust one or more privacy settings of the first social network 101 a and updates the user's privacy settings in the storage device and/or data storage device 110 a. In one embodiment, after the user adjusts one or more privacy settings of the first social network 101 a, a request to notify the user when one or more of the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n is sent.
FIG. 5 illustrates an example of a storage device 214 storing user data 500 including data belonging to User-A 510 a according to one embodiment. In this example, the User-A data 510 a includes data regarding the user's profile 520 a, the user's privacy settings 520 b, and other data 520 n. In one embodiment, the user's privacy settings data 520 b includes the privacy settings for the user's biographic information 530 a, posts 530 b, photos 530 c, and other privacy settings data 530 n.
Method
Referring now to FIG. 4, a flow chart illustrating an embodiment of a method 400 for notifying a first social network user when one or more the user's privacy settings of the first social network 101 a differ from the user's privacy settings of at least one other social network 101 b, 101 n is shown.
The request receiver engine 302 of the differentiation detection module 220 a receives 402 a request to notify the first social network user when one or more the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. As discussed above, in one embodiment the request received 402 is a login request. In another embodiment, the request received 402 is a request to edit the user's privacy settings of the first social network 101 a. In yet another embodiment, the request received 402 is the user selecting a button or hypertext link for requesting a notification when one or more the user's privacy settings of the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n.
The privacy settings retrieval engine 304 of the differentiation detection module 220 a receives 404 the privacy settings from the user's first social network 101 a and the user's privacy settings from at least one other social network 101 b, 101 n. As discussed above, in one embodiment, the data is received 404 from the storage device 214 of one or more of the social network servers 101 a, 101 b, 101 n. In one embodiment, the data is received from the data storage 110 a/110 b/110 n of one or more of the social network servers 101 a, 101 b, 101 n.
The privacy settings differentiator engine 306 of the differentiation detection module 220 a receives the privacy settings received by the privacy settings retrieval engine 304 then compares 406 the user's privacy settings on the first social network 101 a to the user's privacy settings of the at least one other social network 101 b, 101 n and detects 408 one or more differences. In one embodiment, the privacy settings differentiator engine 306 also determines equivalent privacy settings among the first set of privacy settings and second set of privacy settings, wherein the equivalent privacy settings are further compared to determine whether different privacy settings levels exist. For example, a privacy setting in one social network may be called “visibility” while an equivalent privacy setting in a second social network may be called “exposure.” The privacy settings differentiator engine 306 determines that these two settings are equivalent and compares the two for differences.
As discussed above, in one embodiment, the privacy settings differentiator engine 306 compares the user's privacy settings on the first social network 101 a to the user's privacy settings of the at least one other social network 101 b, 101 n until it detects 408 a first difference then stops comparing 406 and detecting 408. In another embodiment, the privacy settings differentiator engine 306 compares 406 all the user's privacy settings on the first social network 101 a to all the user's privacy settings of the at least one other social network 101 b, 101 n and detects 408 all the differences. In one embodiment, the privacy settings differentiator engine 306 detects 408 a difference only when the first social network's 101 a privacy setting is less restrictive than the privacy setting of the at least one other social network 101 b, 101 n.
The differentiation display engine 308 of the differentiation detection module 220 a generates 412 a notification based on any differences detected 408 by the privacy settings differentiator engine 306 and sends 414 the notification for display to the user. In one embodiment, when no difference is detected (410—No), no notification is generated or sent for display to the user. In another embodiment, when no difference is detected (410—No), a notification is generated and sent to the user to notify the user that no differences were detected (not shown).
In one embodiment, when one or more differences are detected (410—Yes), the differentiation display engine 308 generates (412) a notification and sends (410) the notification for display to the user. As discussed above, in one embodiment, the generated 412 notification notifies the user when one or more of the user's privacy settings on the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. In one embodiment, the generated 412 notification includes information about which of the user's privacy settings on the first social network 101 a differ from the user's privacy settings of the at least one other social network 101 b, 101 n. In one embodiment, the generated 412 notification identifies the at least one other social network 101 b, 101 n that has privacy settings that differ from those on the first social network 101 a. In one embodiment, the generated 412 notification includes, for one or more of the privacy settings that differ, what the privacy settings are set to on the first social network 101 a and the at least one other social network 101 b, 101 n.
As discussed above, in one embodiment, the notification gives the user the option to view the user's privacy settings of the user's first social network 101 a by including a link to privacy settings page. In one embodiment, the notification gives the user the option to change the user's privacy settings fn the user's first social network 101 a by including a link to a privacy settings editing page (see FIG. 6). In another embodiment, the notification gives the user the option to adjust the privacy settings of the first social network in the notification (not shown). In one embodiment, the notification requires user to confirm receipt of the notification in order for the notification to close (see FIG. 6).
As mentioned above, the notification may appear in any number of places including, but not limited to, an e-mail, a pop-up, a banner, a separate webpage, or where the privacy settings are typically set or displayed.
Graphical User Interface
FIG. 6 is a graphic representation of an example of a user interface 600 displaying a user's social networking page 602. In one embodiment, the notification 604 appears in a pop-up window 606. In the illustrated example, the notification 604 notifies the first social network user that the user's first social network uses less restrictive privacy settings than the user's other social network 101 b/101 n; however, as previously discussed, the notification 604 can contain different/other information. According to one embodiment, the notification requires user to confirm the receipt of the notification 604 by using the user input device 608 to select a confirmation button 610. According to one embodiment, the notification 604 gives the user the option to edit the user's privacy settings by linking them to the privacy settings edit page, which is accomplished by the “Edit” button 612 in the illustrated embodiment.
FIG. 7 is a graphic representation of a user interface 700 displaying a notification 703 on a separate social networking page 702. In the illustrated embodiment, the notification 703 notifies the user that the first social network's 101 a privacy settings differ from those on one or more of the user's other social networks 101 b, 101 n. As previously discussed, according to one embodiment, the notification 703 can include information about which privacy settings differ and what those settings are. In the illustrated embodiment, table 704 includes information about which privacy settings differ and what each of those settings is. Table 704 includes column 706, which contains the one or more features associated with privacy settings that differ between the user's first social network 101 a and at least one other social network 101 b, 101 n according to one embodiment. Table 704, according to one embodiment, includes column 708, which contains the first social network's 101 a privacy settings associated with each of the one or more features in column 706. Table 704, according to one embodiment, includes column 710, which contains the privacy settings associated with each of the one or more features in column 706 in a first different social network 101 b/101 n to which the user also belongs. Table 704, according to one embodiment, includes column 712, which contains the privacy settings associated with each of the one or more features in column 706 in a second different social network 101 b/101 n to which the user also belongs. In one embodiment, the user is notified which privacy settings are different and how those settings are different by reading across a row in table 704. For example, row 705 notifies the user that the privacy setting for the user's “First/Last Name” varies because the user's first social network has a privacy setting that makes that data and information public, “Other Social Network 1” has a different setting, and “Other Social Network 2's” privacy setting matches that of the first social network in one embodiment. In the illustrated example, box 714 is left empty. In one embodiment, a box is left empty when the privacy setting for that feature on that social network matches the privacy setting for that feature on the user's first social network.
The foregoing description of the embodiments has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the present embodiment to the precise forms disclosed. Many modifications and variations are possible in light of the above teaching. It is intended that the scope of the present embodiments be limited not by this detailed description, but rather by the claims of this application. As will be understood by those familiar with the art, the embodiments may take other specific forms without departing from the spirit or essential characteristics thereof. Likewise, the particular naming and division of the modules, routines, features, attributes, methodologies and other aspects are not mandatory or significant, and the mechanisms that implement one embodiment or its features may have different names, divisions and/or formats. Furthermore, as will be apparent to one of ordinary skill in the relevant art, the modules, routines, features, attributes, methodologies and other aspects of the embodiments can be implemented as software, hardware, firmware or any combination of the three. Also, wherever a component, an example of which is a module, is the component can be implemented as software, the component can be implemented as a standalone program, as part of a larger program, as a plurality of separate programs, as a statically or dynamically linked library, as a kernel loadable module, as a device driver, and/or in every and any other way known now or in the future to those of ordinary skill in the art of computer programming. Additionally, the embodiments are in no way limited to implementation in any specific programming language, or for any specific operating system or environment. Accordingly, the disclosure is intended to be illustrative, but not limiting, of the scope, which is set forth in the following claims.

Claims (18)

What is claimed is:
1. A computer-implemented method comprising:
receiving, using one or more processors, a first set of user privacy settings of a user from a first service and a second set of privacy settings of the user from at least one other service, the first set of privacy settings of the user including user-defined accessibility to one or more features associated with the user of the first service, and the second set of privacy settings of the user including user-defined accessibility to one or more features associated with the user of the at least one other service;
detecting, using the one or more processors, a difference between the first set of privacy settings and the second set of privacy settings, wherein the difference exists when the privacy setting of the first set of privacy settings is less restrictive than the privacy setting of the second set of privacy settings; and
responsive to detecting the difference between the first set of privacy settings and the second set of privacy settings, using one or more processors, performing an action related to the first set of user privacy settings including generating a notification and sending the notification over a network.
2. The method of claim 1, wherein detecting the difference between the first set of privacy settings and the second set of privacy settings comprises:
comparing the first set of privacy settings to the second set of privacy settings; and
determining equivalent privacy settings among the first set of privacy settings and second set of privacy settings; and
comparing the equivalent privacy settings to determine whether different privacy settings levels exist.
3. The method of claim 1, wherein the notification identifies the at least one other service having the detected difference from the first service.
4. The method of claim 1, wherein the notification includes the detected difference between the first set of privacy settings and the second set of privacy settings.
5. The method of claim 1, wherein the notification allows the user to request to view or edit one or more of the privacy settings of the first service.
6. The method of claim 1, wherein performing the action related to the first set of user privacy settings comprises:
receiving from the user a request to view or edit the first set of privacy settings; and
sending the user a webpage on the first service where the first set of privacy settings are typically displayed or edited.
7. The method of claim 1, wherein performing the action related to the first set of user privacy settings, further comprises:
receiving from the user a request to edit and one or more edits to the first set of privacy settings; and
updating the first set of privacy settings according to the one or more edits received from the user.
8. A system comprising:
one or more processors;
a memory storing instructions that, when executed by the one or more processors, cause the system to:
receive a first set of privacy settings of a user from a first service and a second set of privacy settings of the user from at least one other service, the first set of privacy settings of the user including user-defined accessibility to one or more features associated with the user of the first service, and the second set of privacy settings of the user including user-defined accessibility to one or more features associated with the user of the at least one other service;
detect a difference between the first set of privacy settings and the second set of privacy settings, wherein the difference exists when the privacy setting of the first set of privacy settings is less restrictive than the privacy setting of the second set of privacy settings; and
perform an action related to the first set of user privacy settings responsive to the difference between the first set of privacy settings and the second set of privacy settings, the action including generating a notification and sending the notification over a network.
9. The system of claim 8, wherein detecting the difference between the first set of privacy settings and the second set of privacy settings comprises: comparing the first set of privacy settings to the second set of privacy settings, determining equivalent privacy settings among the first set of privacy settings and second set of privacy settings, and comparing the equivalent privacy settings to determine whether different privacy settings levels exist.
10. The system of claim 8,
wherein the notification identifies the at least one other service having the detected difference from the first service.
11. The system of claim 8, wherein the notification includes the detected difference between the first set of privacy settings and the second set of privacy settings.
12. The system of claim 11, wherein the notification allows the user to request to view or edit one or more of the privacy settings of the first service.
13. The system of claim 8, wherein the instructions, when executed, further cause the system to: receive a request from the user to view or edit the first set of privacy settings, and sends the user a webpage on the first service where the first set of privacy settings are typically displayed, or edited.
14. The system of claim 8, wherein the instructions, when executed, further cause the system to:
receive a request from the user to edit and one or more edits to the first set of privacy settings; and
update the first set of privacy settings according to the edits received from the user.
15. A computer-implemented method for generating a notification of privacy settings difference, the method comprising:
receiving, using one or more processors, a request for access to information on a service, wherein the information includes privacy settings information of a user;
receiving, using one or more processors, a first set of user privacy settings of the user from a first service and a second set of privacy settings of the user from at least one other service, wherein the first set of privacy settings of the user include user-defined accessibility to one or more features associated with the user of the first service, and wherein the second set of privacy settings of the user include user-defined accessibility to one or more features associated with the user of the second service;
detecting, using one or more processors, a difference between the first set of privacy settings and the second set of privacy settings, wherein the difference exists when the privacy setting of the first set of privacy settings is less restrictive than the privacy setting of the second set of privacy settings; and
responsive to detecting the difference between the first set of privacy settings and the second set of privacy settings, generating, using one or more processors, a notification that includes an indication that the difference has been detected, and sending the notification over a network.
16. The method of claim 15, wherein the request is the user's login request that is sent to a first social service.
17. The method of claim 15, wherein the request is the user's request to edit the first set of privacy settings.
18. The method of claim 15, wherein the request is the user selecting a button or hypertext link on a first social service.
US14/453,319 2011-06-30 2014-08-06 System and method for privacy setting differentiation detection Active US9294333B1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US14/453,319 US9294333B1 (en) 2011-06-30 2014-08-06 System and method for privacy setting differentiation detection

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US13/173,359 US8832854B1 (en) 2011-06-30 2011-06-30 System and method for privacy setting differentiation detection
US14/453,319 US9294333B1 (en) 2011-06-30 2014-08-06 System and method for privacy setting differentiation detection

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US13/173,359 Continuation US8832854B1 (en) 2011-06-30 2011-06-30 System and method for privacy setting differentiation detection

Publications (1)

Publication Number Publication Date
US9294333B1 true US9294333B1 (en) 2016-03-22

Family

ID=51455428

Family Applications (2)

Application Number Title Priority Date Filing Date
US13/173,359 Active US8832854B1 (en) 2011-06-30 2011-06-30 System and method for privacy setting differentiation detection
US14/453,319 Active US9294333B1 (en) 2011-06-30 2014-08-06 System and method for privacy setting differentiation detection

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US13/173,359 Active US8832854B1 (en) 2011-06-30 2011-06-30 System and method for privacy setting differentiation detection

Country Status (1)

Country Link
US (2) US8832854B1 (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9948651B1 (en) * 2015-12-14 2018-04-17 Symantec Corporation Automatic shared personal image privacy level detection and management
US10419381B2 (en) * 2016-08-30 2019-09-17 Facebook, Inc. Prompt ranking

Families Citing this family (152)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8893287B2 (en) 2012-03-12 2014-11-18 Microsoft Corporation Monitoring and managing user privacy levels
EP2929480A4 (en) * 2012-12-06 2016-10-26 Thomson Licensing Social network privacy auditor
US9471943B2 (en) * 2013-06-20 2016-10-18 Facebook, Inc. User-specified distribution of stories describing user actions in a social networking system
US9729583B1 (en) 2016-06-10 2017-08-08 OneTrust, LLC Data processing systems and methods for performing privacy assessments and monitoring of new versions of computer code for privacy compliance
CN107969154A (en) * 2015-03-06 2018-04-27 诺基亚技术有限公司 Privacy management
US11244367B2 (en) 2016-04-01 2022-02-08 OneTrust, LLC Data processing systems and methods for integrating privacy information management systems with data loss prevention tools or other tools for privacy design
US10706447B2 (en) 2016-04-01 2020-07-07 OneTrust, LLC Data processing systems and communication systems and methods for the efficient generation of privacy risk assessments
US20220164840A1 (en) 2016-04-01 2022-05-26 OneTrust, LLC Data processing systems and methods for integrating privacy information management systems with data loss prevention tools or other tools for privacy design
US11004125B2 (en) 2016-04-01 2021-05-11 OneTrust, LLC Data processing systems and methods for integrating privacy information management systems with data loss prevention tools or other tools for privacy design
US11651104B2 (en) 2016-06-10 2023-05-16 OneTrust, LLC Consent receipt management systems and related methods
US11038925B2 (en) 2016-06-10 2021-06-15 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US11727141B2 (en) 2016-06-10 2023-08-15 OneTrust, LLC Data processing systems and methods for synching privacy-related user consent across multiple computing devices
US11227247B2 (en) 2016-06-10 2022-01-18 OneTrust, LLC Data processing systems and methods for bundled privacy policies
US11134086B2 (en) 2016-06-10 2021-09-28 OneTrust, LLC Consent conversion optimization systems and related methods
US10706174B2 (en) 2016-06-10 2020-07-07 OneTrust, LLC Data processing systems for prioritizing data subject access requests for fulfillment and related methods
US10909265B2 (en) 2016-06-10 2021-02-02 OneTrust, LLC Application privacy scanning systems and related methods
US10454973B2 (en) 2016-06-10 2019-10-22 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US10642870B2 (en) 2016-06-10 2020-05-05 OneTrust, LLC Data processing systems and methods for automatically detecting and documenting privacy-related aspects of computer software
US10169609B1 (en) 2016-06-10 2019-01-01 OneTrust, LLC Data processing systems for fulfilling data subject access requests and related methods
US11151233B2 (en) 2016-06-10 2021-10-19 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US10853501B2 (en) 2016-06-10 2020-12-01 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US10726158B2 (en) 2016-06-10 2020-07-28 OneTrust, LLC Consent receipt management and automated process blocking systems and related methods
US11087260B2 (en) 2016-06-10 2021-08-10 OneTrust, LLC Data processing systems and methods for customizing privacy training
US10503926B2 (en) 2016-06-10 2019-12-10 OneTrust, LLC Consent receipt management systems and related methods
US10769301B2 (en) 2016-06-10 2020-09-08 OneTrust, LLC Data processing systems for webform crawling to map processing activities and related methods
US11438386B2 (en) 2016-06-10 2022-09-06 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US11586700B2 (en) 2016-06-10 2023-02-21 OneTrust, LLC Data processing systems and methods for automatically blocking the use of tracking tools
US10318761B2 (en) 2016-06-10 2019-06-11 OneTrust, LLC Data processing systems and methods for auditing data request compliance
US10776517B2 (en) 2016-06-10 2020-09-15 OneTrust, LLC Data processing systems for calculating and communicating cost of fulfilling data subject access requests and related methods
US10997315B2 (en) 2016-06-10 2021-05-04 OneTrust, LLC Data processing systems for fulfilling data subject access requests and related methods
US10685140B2 (en) 2016-06-10 2020-06-16 OneTrust, LLC Consent receipt management systems and related methods
US11625502B2 (en) 2016-06-10 2023-04-11 OneTrust, LLC Data processing systems for identifying and modifying processes that are subject to data subject access requests
US11475136B2 (en) 2016-06-10 2022-10-18 OneTrust, LLC Data processing systems for data transfer risk identification and related methods
US10944725B2 (en) 2016-06-10 2021-03-09 OneTrust, LLC Data processing systems and methods for using a data model to select a target data asset in a data migration
US10740487B2 (en) 2016-06-10 2020-08-11 OneTrust, LLC Data processing systems and methods for populating and maintaining a centralized database of personal data
US11366909B2 (en) 2016-06-10 2022-06-21 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US10848523B2 (en) 2016-06-10 2020-11-24 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US10839102B2 (en) 2016-06-10 2020-11-17 OneTrust, LLC Data processing systems for identifying and modifying processes that are subject to data subject access requests
US10565236B1 (en) 2016-06-10 2020-02-18 OneTrust, LLC Data processing systems for generating and populating a data inventory
US10678945B2 (en) 2016-06-10 2020-06-09 OneTrust, LLC Consent receipt management systems and related methods
US11222142B2 (en) 2016-06-10 2022-01-11 OneTrust, LLC Data processing systems for validating authorization for personal data collection, storage, and processing
US10467432B2 (en) 2016-06-10 2019-11-05 OneTrust, LLC Data processing systems for use in automatically generating, populating, and submitting data subject access requests
US10776518B2 (en) 2016-06-10 2020-09-15 OneTrust, LLC Consent receipt management systems and related methods
US11416798B2 (en) 2016-06-10 2022-08-16 OneTrust, LLC Data processing systems and methods for providing training in a vendor procurement process
US11025675B2 (en) 2016-06-10 2021-06-01 OneTrust, LLC Data processing systems and methods for performing privacy assessments and monitoring of new versions of computer code for privacy compliance
US10510031B2 (en) 2016-06-10 2019-12-17 OneTrust, LLC Data processing systems for identifying, assessing, and remediating data processing risks using data modeling techniques
US11328092B2 (en) 2016-06-10 2022-05-10 OneTrust, LLC Data processing systems for processing and managing data subject access in a distributed environment
US11138242B2 (en) 2016-06-10 2021-10-05 OneTrust, LLC Data processing systems and methods for automatically detecting and documenting privacy-related aspects of computer software
US10242228B2 (en) 2016-06-10 2019-03-26 OneTrust, LLC Data processing systems for measuring privacy maturity within an organization
US10846433B2 (en) 2016-06-10 2020-11-24 OneTrust, LLC Data processing consent management systems and related methods
US11228620B2 (en) 2016-06-10 2022-01-18 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US11410106B2 (en) 2016-06-10 2022-08-09 OneTrust, LLC Privacy management systems and methods
US10509920B2 (en) 2016-06-10 2019-12-17 OneTrust, LLC Data processing systems for processing data subject access requests
US10796260B2 (en) 2016-06-10 2020-10-06 OneTrust, LLC Privacy management systems and methods
US11074367B2 (en) 2016-06-10 2021-07-27 OneTrust, LLC Data processing systems for identity validation for consumer rights requests and related methods
US11544667B2 (en) 2016-06-10 2023-01-03 OneTrust, LLC Data processing systems for generating and populating a data inventory
US10586075B2 (en) 2016-06-10 2020-03-10 OneTrust, LLC Data processing systems for orphaned data identification and deletion and related methods
US11200341B2 (en) 2016-06-10 2021-12-14 OneTrust, LLC Consent receipt management systems and related methods
US10585968B2 (en) 2016-06-10 2020-03-10 OneTrust, LLC Data processing systems for fulfilling data subject access requests and related methods
US10565161B2 (en) 2016-06-10 2020-02-18 OneTrust, LLC Data processing systems for processing data subject access requests
US11295316B2 (en) 2016-06-10 2022-04-05 OneTrust, LLC Data processing systems for identity validation for consumer rights requests and related methods
US11562097B2 (en) 2016-06-10 2023-01-24 OneTrust, LLC Data processing systems for central consent repository and related methods
US11520928B2 (en) 2016-06-10 2022-12-06 OneTrust, LLC Data processing systems for generating personal data receipts and related methods
US10496803B2 (en) 2016-06-10 2019-12-03 OneTrust, LLC Data processing systems and methods for efficiently assessing the risk of privacy campaigns
US11675929B2 (en) 2016-06-10 2023-06-13 OneTrust, LLC Data processing consent sharing systems and related methods
US12118121B2 (en) 2016-06-10 2024-10-15 OneTrust, LLC Data subject access request processing systems and related methods
US12045266B2 (en) 2016-06-10 2024-07-23 OneTrust, LLC Data processing systems for generating and populating a data inventory
US11651106B2 (en) 2016-06-10 2023-05-16 OneTrust, LLC Data processing systems for fulfilling data subject access requests and related methods
US10607028B2 (en) 2016-06-10 2020-03-31 OneTrust, LLC Data processing systems for data testing to confirm data deletion and related methods
US10592692B2 (en) 2016-06-10 2020-03-17 OneTrust, LLC Data processing systems for central consent repository and related methods
US11210420B2 (en) 2016-06-10 2021-12-28 OneTrust, LLC Data subject access request processing systems and related methods
US10949170B2 (en) 2016-06-10 2021-03-16 OneTrust, LLC Data processing systems for integration of consumer feedback with data subject access requests and related methods
US11138299B2 (en) 2016-06-10 2021-10-05 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US11636171B2 (en) 2016-06-10 2023-04-25 OneTrust, LLC Data processing user interface monitoring systems and related methods
US10885485B2 (en) 2016-06-10 2021-01-05 OneTrust, LLC Privacy management systems and methods
US11392720B2 (en) 2016-06-10 2022-07-19 OneTrust, LLC Data processing systems for verification of consent and notice processing and related methods
US10878127B2 (en) 2016-06-10 2020-12-29 OneTrust, LLC Data subject access request processing systems and related methods
US11301796B2 (en) 2016-06-10 2022-04-12 OneTrust, LLC Data processing systems and methods for customizing privacy training
US11144622B2 (en) 2016-06-10 2021-10-12 OneTrust, LLC Privacy management systems and methods
US10909488B2 (en) 2016-06-10 2021-02-02 OneTrust, LLC Data processing systems for assessing readiness for responding to privacy-related incidents
US11222139B2 (en) 2016-06-10 2022-01-11 OneTrust, LLC Data processing systems and methods for automatic discovery and assessment of mobile software development kits
US11057356B2 (en) 2016-06-10 2021-07-06 OneTrust, LLC Automated data processing systems and methods for automatically processing data subject access requests using a chatbot
US10496846B1 (en) * 2016-06-10 2019-12-03 OneTrust, LLC Data processing and communications systems and methods for the efficient implementation of privacy by design
US11416109B2 (en) 2016-06-10 2022-08-16 OneTrust, LLC Automated data processing systems and methods for automatically processing data subject access requests using a chatbot
US11238390B2 (en) 2016-06-10 2022-02-01 OneTrust, LLC Privacy management systems and methods
US10896394B2 (en) 2016-06-10 2021-01-19 OneTrust, LLC Privacy management systems and methods
US10708305B2 (en) 2016-06-10 2020-07-07 OneTrust, LLC Automated data processing systems and methods for automatically processing requests for privacy-related information
US11146566B2 (en) 2016-06-10 2021-10-12 OneTrust, LLC Data processing systems for fulfilling data subject access requests and related methods
US10803200B2 (en) 2016-06-10 2020-10-13 OneTrust, LLC Data processing systems for processing and managing data subject access in a distributed environment
US10762236B2 (en) 2016-06-10 2020-09-01 OneTrust, LLC Data processing user interface monitoring systems and related methods
US10706131B2 (en) 2016-06-10 2020-07-07 OneTrust, LLC Data processing systems and methods for efficiently assessing the risk of privacy campaigns
US10873606B2 (en) 2016-06-10 2020-12-22 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US10606916B2 (en) 2016-06-10 2020-03-31 OneTrust, LLC Data processing user interface monitoring systems and related methods
US11416589B2 (en) 2016-06-10 2022-08-16 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US10592648B2 (en) 2016-06-10 2020-03-17 OneTrust, LLC Consent receipt management systems and related methods
US10783256B2 (en) 2016-06-10 2020-09-22 OneTrust, LLC Data processing systems for data transfer risk identification and related methods
US11366786B2 (en) 2016-06-10 2022-06-21 OneTrust, LLC Data processing systems for processing data subject access requests
US10997318B2 (en) 2016-06-10 2021-05-04 OneTrust, LLC Data processing systems for generating and populating a data inventory for processing data access requests
US11188615B2 (en) 2016-06-10 2021-11-30 OneTrust, LLC Data processing consent capture systems and related methods
US10353673B2 (en) 2016-06-10 2019-07-16 OneTrust, LLC Data processing systems for integration of consumer feedback with data subject access requests and related methods
US10284604B2 (en) 2016-06-10 2019-05-07 OneTrust, LLC Data processing and scanning systems for generating and populating a data inventory
US11403377B2 (en) 2016-06-10 2022-08-02 OneTrust, LLC Privacy management systems and methods
US11336697B2 (en) 2016-06-10 2022-05-17 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US11354435B2 (en) 2016-06-10 2022-06-07 OneTrust, LLC Data processing systems for data testing to confirm data deletion and related methods
US10706176B2 (en) 2016-06-10 2020-07-07 OneTrust, LLC Data-processing consent refresh, re-prompt, and recapture systems and related methods
US10798133B2 (en) 2016-06-10 2020-10-06 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US11023842B2 (en) 2016-06-10 2021-06-01 OneTrust, LLC Data processing systems and methods for bundled privacy policies
US10572686B2 (en) 2016-06-10 2020-02-25 OneTrust, LLC Consent receipt management systems and related methods
US10416966B2 (en) 2016-06-10 2019-09-17 OneTrust, LLC Data processing systems for identity validation of data subject access requests and related methods
US10614247B2 (en) 2016-06-10 2020-04-07 OneTrust, LLC Data processing systems for automated classification of personal information from documents and related methods
US11418492B2 (en) 2016-06-10 2022-08-16 OneTrust, LLC Data processing systems and methods for using a data model to select a target data asset in a data migration
US11461500B2 (en) 2016-06-10 2022-10-04 OneTrust, LLC Data processing systems for cookie compliance testing with website scanning and related methods
US10713387B2 (en) 2016-06-10 2020-07-14 OneTrust, LLC Consent conversion optimization systems and related methods
US12052289B2 (en) 2016-06-10 2024-07-30 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US11157600B2 (en) 2016-06-10 2021-10-26 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US11354434B2 (en) 2016-06-10 2022-06-07 OneTrust, LLC Data processing systems for verification of consent and notice processing and related methods
US11481710B2 (en) 2016-06-10 2022-10-25 OneTrust, LLC Privacy management systems and methods
US11343284B2 (en) 2016-06-10 2022-05-24 OneTrust, LLC Data processing systems and methods for performing privacy assessments and monitoring of new versions of computer code for privacy compliance
US10565397B1 (en) 2016-06-10 2020-02-18 OneTrust, LLC Data processing systems for fulfilling data subject access requests and related methods
US11416590B2 (en) 2016-06-10 2022-08-16 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US11341447B2 (en) 2016-06-10 2022-05-24 OneTrust, LLC Privacy management systems and methods
US11222309B2 (en) 2016-06-10 2022-01-11 OneTrust, LLC Data processing systems for generating and populating a data inventory
US10282700B2 (en) 2016-06-10 2019-05-07 OneTrust, LLC Data processing systems for generating and populating a data inventory
US11188862B2 (en) 2016-06-10 2021-11-30 OneTrust, LLC Privacy management systems and methods
US10282559B2 (en) 2016-06-10 2019-05-07 OneTrust, LLC Data processing systems for identifying, assessing, and remediating data processing risks using data modeling techniques
US11277448B2 (en) 2016-06-10 2022-03-15 OneTrust, LLC Data processing systems for data-transfer risk identification, cross-border visualization generation, and related methods
US10706379B2 (en) 2016-06-10 2020-07-07 OneTrust, LLC Data processing systems for automatic preparation for remediation and related methods
US11100444B2 (en) 2016-06-10 2021-08-24 OneTrust, LLC Data processing systems and methods for providing training in a vendor procurement process
US10949565B2 (en) 2016-06-10 2021-03-16 OneTrust, LLC Data processing systems for generating and populating a data inventory
US10509894B2 (en) 2016-06-10 2019-12-17 OneTrust, LLC Data processing and scanning systems for assessing vendor risk
US10776514B2 (en) 2016-06-10 2020-09-15 OneTrust, LLC Data processing systems for the identification and deletion of personal data in computer systems
US11294939B2 (en) 2016-06-10 2022-04-05 OneTrust, LLC Data processing systems and methods for automatically detecting and documenting privacy-related aspects of computer software
US10013577B1 (en) 2017-06-16 2018-07-03 OneTrust, LLC Data processing systems for identifying whether cookies contain personally identifying information
US10803202B2 (en) 2018-09-07 2020-10-13 OneTrust, LLC Data processing systems for orphaned data identification and deletion and related methods
US11544409B2 (en) 2018-09-07 2023-01-03 OneTrust, LLC Data processing systems and methods for automatically protecting sensitive data within privacy management systems
US11144675B2 (en) 2018-09-07 2021-10-12 OneTrust, LLC Data processing systems and methods for automatically protecting sensitive data within privacy management systems
US11797528B2 (en) 2020-07-08 2023-10-24 OneTrust, LLC Systems and methods for targeted data discovery
WO2022026564A1 (en) 2020-07-28 2022-02-03 OneTrust, LLC Systems and methods for automatically blocking the use of tracking tools
WO2022032072A1 (en) 2020-08-06 2022-02-10 OneTrust, LLC Data processing systems and methods for automatically redacting unstructured data from a data subject access request
US11436373B2 (en) 2020-09-15 2022-09-06 OneTrust, LLC Data processing systems and methods for detecting tools for the automatic blocking of consent requests
WO2022061270A1 (en) 2020-09-21 2022-03-24 OneTrust, LLC Data processing systems and methods for automatically detecting target data transfers and target data processing
US11397819B2 (en) 2020-11-06 2022-07-26 OneTrust, LLC Systems and methods for identifying data processing activities based on data discovery results
US11687528B2 (en) 2021-01-25 2023-06-27 OneTrust, LLC Systems and methods for discovery, classification, and indexing of data in a native computing system
WO2022170047A1 (en) 2021-02-04 2022-08-11 OneTrust, LLC Managing custom attributes for domain objects defined within microservices
US11494515B2 (en) 2021-02-08 2022-11-08 OneTrust, LLC Data processing systems and methods for anonymizing data samples in classification analysis
US20240098109A1 (en) 2021-02-10 2024-03-21 OneTrust, LLC Systems and methods for mitigating risks of third-party computing system functionality integration into a first-party computing system
WO2022178089A1 (en) 2021-02-17 2022-08-25 OneTrust, LLC Managing custom workflows for domain objects defined within microservices
WO2022178219A1 (en) 2021-02-18 2022-08-25 OneTrust, LLC Selective redaction of media content
US11533315B2 (en) 2021-03-08 2022-12-20 OneTrust, LLC Data transfer discovery and analysis systems and related methods
US11562078B2 (en) 2021-04-16 2023-01-24 OneTrust, LLC Assessing and managing computational risk involved with integrating third party computing functionality within a computing system
US20230196479A1 (en) * 2021-12-21 2023-06-22 Meta Platforms, Inc. Collaborative stories
US11620142B1 (en) 2022-06-03 2023-04-04 OneTrust, LLC Generating and customizing user interfaces for demonstrating functions of interactive user environments

Citations (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6130938A (en) 1996-07-08 2000-10-10 Mitel Corporation Automatic call forwarding
US6192119B1 (en) 1996-03-04 2001-02-20 Intellprop Limited Telephone conferencing systems
US20020137490A1 (en) 2001-03-20 2002-09-26 Worldcom, Inc. Call forwarding on screening
US20020143874A1 (en) 2001-03-30 2002-10-03 Brian Marquette Media session framework using a control module to direct and manage application and service servers
WO2002079984A1 (en) 2001-03-20 2002-10-10 Worldcom, Inc. Integration platform and provisioning server communication systems
US6697478B1 (en) 2000-09-20 2004-02-24 Parallel Communications, Inc. Simultaneous telephone ring apparatus and method
US6754322B1 (en) 1999-08-31 2004-06-22 William Jackson Bushnell Call me conference call system
US20040258220A1 (en) 2002-03-29 2004-12-23 Levine David A. Method and system for screening calls during voicemail messaging
US20050152521A1 (en) 2000-02-25 2005-07-14 Liljestrand Keith A. Apparatus and method for providing enhanced telecommunications services
US20060026288A1 (en) 2004-07-30 2006-02-02 Arup Acharya Method and apparatus for integrating wearable devices within a SIP infrastructure
US20060077957A1 (en) 2004-10-08 2006-04-13 Umamaheswar Reddy Call handoff between subscriber's multiple devices associated with multiple networks
US7106848B1 (en) 2002-06-07 2006-09-12 At&T Corp. Method and apparatus for in-progress call forwarding
US20060206604A1 (en) 2005-03-14 2006-09-14 O'neil Douglas R Methods and systems for providing a communication manager for wireless wireline converged telecommunication services
US20070127631A1 (en) 2005-12-02 2007-06-07 General Instrument Corporation Method and apparatus for bridging between voicemail and electronic message media types in a communication system
US20070171898A1 (en) 2005-11-29 2007-07-26 Salva Paul D System and method for establishing universal real time protocol bridging
US20070173236A1 (en) 2006-01-24 2007-07-26 Envio Networks Inc. Methods for Marketing Digital Content to Mobile Communication Device Users
US20070248077A1 (en) 2006-04-20 2007-10-25 Fusion Telecommunications International, Inc. Distributed voice over internet protocol apparatus and systems
US20080056475A1 (en) 2006-09-06 2008-03-06 Genband Inc. Methods, systems, and computer program products for flexible call jumping
US7366990B2 (en) 2001-01-19 2008-04-29 C-Sam, Inc. Method and system for managing user activities and information using a customized computer interface
US20080192656A1 (en) 2007-02-09 2008-08-14 Ted Vagelos Systems And Methods For Providing Enhanced Telephone Services
US7555110B2 (en) 1999-04-01 2009-06-30 Callwave, Inc. Methods and apparatus for providing expanded telecommunications service
US20090171964A1 (en) 2008-01-02 2009-07-02 George Eberstadt Acquiring And Using Social Network Information
US7610287B1 (en) 2005-06-28 2009-10-27 Google Inc. System and method for impromptu shared communication spaces
US20110098156A1 (en) 2009-10-26 2011-04-28 Apple Inc. Systems and methods for accessing personalized fitness services using a portable electronic device

Patent Citations (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6192119B1 (en) 1996-03-04 2001-02-20 Intellprop Limited Telephone conferencing systems
US6130938A (en) 1996-07-08 2000-10-10 Mitel Corporation Automatic call forwarding
US7555110B2 (en) 1999-04-01 2009-06-30 Callwave, Inc. Methods and apparatus for providing expanded telecommunications service
US6754322B1 (en) 1999-08-31 2004-06-22 William Jackson Bushnell Call me conference call system
US20050152521A1 (en) 2000-02-25 2005-07-14 Liljestrand Keith A. Apparatus and method for providing enhanced telecommunications services
US6697478B1 (en) 2000-09-20 2004-02-24 Parallel Communications, Inc. Simultaneous telephone ring apparatus and method
US7366990B2 (en) 2001-01-19 2008-04-29 C-Sam, Inc. Method and system for managing user activities and information using a customized computer interface
WO2002079984A1 (en) 2001-03-20 2002-10-10 Worldcom, Inc. Integration platform and provisioning server communication systems
US20020137490A1 (en) 2001-03-20 2002-09-26 Worldcom, Inc. Call forwarding on screening
US20020143874A1 (en) 2001-03-30 2002-10-03 Brian Marquette Media session framework using a control module to direct and manage application and service servers
US20040258220A1 (en) 2002-03-29 2004-12-23 Levine David A. Method and system for screening calls during voicemail messaging
US7106848B1 (en) 2002-06-07 2006-09-12 At&T Corp. Method and apparatus for in-progress call forwarding
US20060026288A1 (en) 2004-07-30 2006-02-02 Arup Acharya Method and apparatus for integrating wearable devices within a SIP infrastructure
US20060077957A1 (en) 2004-10-08 2006-04-13 Umamaheswar Reddy Call handoff between subscriber's multiple devices associated with multiple networks
US20060206604A1 (en) 2005-03-14 2006-09-14 O'neil Douglas R Methods and systems for providing a communication manager for wireless wireline converged telecommunication services
US7610287B1 (en) 2005-06-28 2009-10-27 Google Inc. System and method for impromptu shared communication spaces
US20070171898A1 (en) 2005-11-29 2007-07-26 Salva Paul D System and method for establishing universal real time protocol bridging
US20070127631A1 (en) 2005-12-02 2007-06-07 General Instrument Corporation Method and apparatus for bridging between voicemail and electronic message media types in a communication system
US20070173236A1 (en) 2006-01-24 2007-07-26 Envio Networks Inc. Methods for Marketing Digital Content to Mobile Communication Device Users
US20070248077A1 (en) 2006-04-20 2007-10-25 Fusion Telecommunications International, Inc. Distributed voice over internet protocol apparatus and systems
US20080056475A1 (en) 2006-09-06 2008-03-06 Genband Inc. Methods, systems, and computer program products for flexible call jumping
US20080192656A1 (en) 2007-02-09 2008-08-14 Ted Vagelos Systems And Methods For Providing Enhanced Telephone Services
US7742468B2 (en) 2007-02-09 2010-06-22 Frontier Communications Corporation Systems and methods for providing enhanced telephone services
US20090171964A1 (en) 2008-01-02 2009-07-02 George Eberstadt Acquiring And Using Social Network Information
US20110098156A1 (en) 2009-10-26 2011-04-28 Apple Inc. Systems and methods for accessing personalized fitness services using a portable electronic device

Non-Patent Citations (34)

* Cited by examiner, † Cited by third party
Title
Adamic et al., "A Social Network Caught in the Web," Internet Journal, First Monday, Jun. 2, 2003, vol. 8, No. 6, pp. 1-22.
Agarwal et al., "Enabling Real-Time User Interests for Next Generation Activity-Oriented Social Networks," Thesis submitted to the Indian Institute of Technology Delhi, Department of Computer Science & Engineering, 2005, 70 pgs.
Anwar et al., "Leveraging 'Social-Network' Infrastructure to Improve Peer-to Peer Overlay Performance: Results from Orkut," University of Illinois at Urbana-Champaign USA, 2005, 9 pgs.
AT&T Personal Reach Service: Benefits and Features, Mar. 29, 2010, 7 pgs.
AT&T Personal Reach Service: Personal Reach Service, Mar. 29, 2010, 2 pgs.
Baird et al., "Neomillennial User Experience Design Strategies: Utilizing Social Networking Media to Support "Always on" Learning Styles," J. Educational Technology Systems, vol. 34(1), 2005-2006, Baywood Publishing Co., Inc., pp. 5-32.
Boyd, et al., "Social Network Sites: Definition, History, and Scholarship," Journal of Computer-Mediated Communication, International Communication Association, 2008, pp. 210-230.
Churchill et al., "Social Networks and Social Networking," IEEE Computer Society, Sep.-Oct. 2005, pp. 14-19.
Cohen et al., "Social Networks for Creative Collaboration," C&C 'OS, Apr. 12-15, 2005, London, United Kingdom, pp. 252-255.
Decker et al., "The Social Semantic Desktop," Digital Enterprise Research Institute, DERI Galway, Ireland, DERI Innsbruck, Austria, DERI Technical Report, May 2, 2004, 7 pgs.
Dukes-Schlossberg et al., "Battlefield Awareness and Data Dissemination Intelligent Information Dissemination Server," Air Force Research Laboratory, Rome Research Site, Rome, NY, Nov. 1, 1999, 31 pgs.
Eagle et al., "Social Serendipity: Proximity Sensing and Cueing," MIT Media Laboratory Technical Note 580, May 2004, 18 pgs.
Erickson et al., "Social Translucence: Using Minimalist Visualizations of Social Activity to Support Collective Interaction," Designing Information Spaces: The Social Navigation Approach, Springerverlag: London, 2003, pp. 1-19.
Gross et al., "Information Revelation and Privacy in Online Social Networks, "WPES 'OS, Alexandria, Virginia, Nov. 7, 2005, pp. 71-80.
Hanunond et al., "Social Bookmarking Tools (I)," D-Lib Magazine, Apr. 2005, vol. II, No. 4, ISSN 1082-9873, 23 pgs.
Heer et al., "Vizster: Visualizing Online Social Networks," University of California, Berkeley, Oct. 23, 2005, 8 pgs.
International Search Report, International Application No. PCT/US2008/005118, Sep. 30, 2008, 2 pgs.
Leonard, "You Are Who You Know," Internet, retrieved at http://www.salon.com. Jun. 15, 2004, 15 pgs.
LiveJournal, "FAQ #163: How Do I Find a Syndicated Account?" Last Updated: thebubba, Jan. 6, 2004, 2 pgs.
Marwick, "Selling Your Self: Online Identity in the Age of a Commodified Internet," University of Washington, 2005, 192 pgs.
MediaSift Ltd., DataSift: Realtime Social Data Mining Platform, Curate and Data Mine the Real Time Web with DataSift, Dedipower, Managed Hosting, [Retrieved on May 13, 2011], 1 pg.
Metcalf et al., "Spatial Dynamics of Social Network Evolution," 23rd International Conference of the System Dynamics Society, Jul. 19, 2005, pp. 1-13.
Mori et al., "Real-world Oriented Information Sharing Using Social Networks," Group 'OS, Sanibel Island, Florida, USA, Nov. 6-9, 2005, pp. 81-84.
Nardi et al., "Blogging as Social Activity, or, Would You Let 900 Million People Read Your Diary?" CSCW'04, Nov. 6-10, 2004, vol. 6, Issue 3, Chicago, Illinois, pp. 222-231.
Neumann et al., "Semantic social network portal for collaborative online communities," Journal of European Industrial Training, 2005, Emerald Group Publishing, Limited, vol. 29, No. 6, pp. 472-487.
O'Murchu et al., "Online Social and Business Networking Communities," Digital Enterprise Research Institute DERI Technical Report, National University of Ireland, Aug. 11, 2004, 22 pgs.
Ring Central, Inc., Internet, retrieved at http://www.ringcentrai.com. Apr. 19, 2007, 1 pg.
Singh et al., "CINEMA: Columbia InterNet Extensible Multimedia Architecture," Department of Computer Science, Columbia University, May 2002, pp. 1-83.
Steen et al., "Development of we-centric, context-aware, adaptive mobile services requires empathy and dialogue," Freeband FRUX, Oct. 17, 2005, Internet Journal, Netherlands, pp. 1-4.
Superfeedr Track, Internet, retrieved at http://blog.superfeedr.com/tracklfilter/xmpp/pubsubhubbub/track, May 13, 2011, 8 pgs.
Twitter Announces Fire Hose Marketplace: Up to 10K Keyword Filters for 30 Cents, Internet, retrieved at http://www.readywriteweb.com/archives/twitter-announces-fire-hose-marketplace-up-to-10k.php, May 13, 2011, 7 pgs.
Twitter Blog: Tracking Twitter, Internet, retrieved at http://blog.twitter.com/2007/09/tracking-twitter.html, May 13, 2011, 2 pgs.
Van Eijk et al., "We-centric, context-aware, adaptive mobile service bundles," Freeband, Telematica Instituut, TNO telecom, Nov. 30, 2004, 48 pgs.
Wenger et al., "Technology for Communities," CEFRIO Book Chapter v5.2, Jan. 18, 2005, pp. 1-15.

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9948651B1 (en) * 2015-12-14 2018-04-17 Symantec Corporation Automatic shared personal image privacy level detection and management
US10419381B2 (en) * 2016-08-30 2019-09-17 Facebook, Inc. Prompt ranking

Also Published As

Publication number Publication date
US8832854B1 (en) 2014-09-09

Similar Documents

Publication Publication Date Title
US9294333B1 (en) System and method for privacy setting differentiation detection
US9224009B1 (en) System and method for applying privacy settings to a plurality of applications
US9276923B1 (en) Generating authentication challenges based on preferences of a user's contacts
US9325655B1 (en) User notification digestion
US8996631B1 (en) Customizing annotations for online content
US9760701B1 (en) Secondary user authentication bypass based on a whitelisting deviation from a user pattern
US9348981B1 (en) System and method for generating user authentication challenges
US8909711B1 (en) System and method for generating privacy-enhanced aggregate statistics
US10511496B2 (en) Method, system and computer program product for interception, quarantine and moderation of internal communications of uncontrolled systems
US9037864B1 (en) Generating authentication challenges based on social network activity information
US20160381064A1 (en) Managing data privacy and information safety
US8510660B2 (en) Method and system for tagging content
US9853926B2 (en) Methods and systems for exchanging private messages
US9203826B1 (en) Authentication based on peer attestation
AU2014240569B2 (en) Image cropping according to points of interest
US20120011451A1 (en) Selective screen sharing
US9094461B2 (en) Filtering a stream of content
US10893052B1 (en) Duress password for limited account access
US9317807B1 (en) Various ways to automatically select sharing settings
US20200021564A9 (en) Mention identification for untrusted content
WO2014062324A2 (en) Generating an animated preview of a multi-party video communication session
US20200014652A1 (en) Message Data Transfer
US11902237B2 (en) Security and prevention of information harvesting from user interfaces
US10243992B2 (en) Secure content delivery over a domain portal
US20170310629A1 (en) Providing Reverse Preference Designations In a Network

Legal Events

Date Code Title Description
AS Assignment

Owner name: GOOGLE INC., CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:STADDON, JESSICA;MCPHIE, JONATHAN S.;REEL/FRAME:033967/0446

Effective date: 20110629

STCF Information on status: patent grant

Free format text: PATENTED CASE

AS Assignment

Owner name: GOOGLE LLC, CALIFORNIA

Free format text: CHANGE OF NAME;ASSIGNOR:GOOGLE INC.;REEL/FRAME:044566/0657

Effective date: 20170929

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 4TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1551); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Year of fee payment: 4

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1552); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Year of fee payment: 8